The Swiggy Data Scientist interview guide, interview questions, salary data, and interview experiences.

Swiggy Data Scientist Interview Guide

Getting ready for an Data Scientist interview at Swiggy? The Swiggy Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for Swiggy Data Scientist roles.</li>
<li>Gain insights into the Data Scientist interview process at Swiggy.</li>
<li>Practice real Swiggy Data Scientist interview questions.</li>
</ul>
Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the Swiggy Data Scientist interview.


Getting ready for an Data Scientist interview at Swiggy? The Swiggy Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:

- Know what skills are necessary for Swiggy Data Scientist roles.
- Gain insights into the Data Scientist interview process at Swiggy.
- Practice real Swiggy Data Scientist interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the Swiggy Data Scientist interview.
        

Overview

We've gathered this data from parsing thousands of interview experiences sourced from members.

We've gathered this data from parsing thousands of interview experiences sourced from members.

Swiggy Data Scientist Interview Process

You are given an array of numerical values, bootstrap samples, and size for a confidence interval.

Write a function that performs bootstrap sampling on the given array and calculates the confidence interval based on the given size.

Note: The function should return a tuple containing the minimum and maximum values of the confidence interval rounded to the tenths place.

Example

Input:

<pre tabindex="0" class="chroma"><code>values = [1, 2, 3, 4, 5]
</code></pre>

Output

<pre tabindex="0" class="chroma"><code>bootstrap_conf_interval(values, 1000, 0.95) -&gt; (1.2, 4.8)
</code></pre>

In this case, the function returns a tuple indicating that we are 95% confident that the population parameter lies between 1.2 and 4.8 based on our bootstrap samples.

Note: Results may vary due to the randomness of bootstrap sampling.

Write a function to bootstrap the confidence interface for a list of integers

Bootstrapping Confidence Intervals

Statistics

Let’s say you’ve just started as the operations manager at Lyft, and the CEO has asked you to design a dashboard for weekly leadership meetings. The company is facing increased competition in major cities, and there’s concern about both driver retention and rider wait times. This week, marketing is launching a $2M campaign to boost new rider signups in these cities.

Given limited dashboard space, what specific metrics and visualizations would you include?

Which metrics and visualizations would you prioritize for a CEO-facing dashboard during a major rider acquisition campaign?

Lyft Ops Dashboard

Data Visualization & Dashboarding

You are given a string that resembles the declaration of a list of dictionaries.

Without using the <code>pandas</code> package, write a function <code>read_split_from_str</code> to split the data into two lists, one for training and one for testing, with a 70:30 split between the training set and the testing set.

Note: Use <code>numpy</code> for random number generation if you need to.

Example

Input:

<pre tabindex="0" class="chroma"><code>list_of_dict_str = &#34;[{&#39;x&#39;: 0.0, &#39;y&#39;: 5.43}, {&#39;x&#39;: 50.0, &#39;y&#39;: 102.78}, {&#39;x&#39;: 100.0, &#39;y&#39;: 204.24}]&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def read_split_from_str(list_of_dict_str) -&gt; 
 [
 [{&#39;x&#39;: 0.0, &#39;y&#39;: 5.43}, {&#39;x&#39;: 50.0, &#39;y&#39;: 102.78}],
 [{&#39;x&#39;: 100.0, &#39;y&#39;: 204.24}]
 ]
</code></pre>

Write a function that splits the data into two lists, one for training and one for testing.

Split Data Without Pandas

Python & General Programming

Swiggy Data Scientist Interview Questions

Data Scientist – Energy Markets & ForecastingLocation: London (Hybrid, 2–3 days per week)Compensation: £Competitive + EquitySector: Climate Tech | Tier-1 VC Backed | Real-Time SystemsI’m working with a cutting-edge climate tech startup that’s focused on decarbonising the energy grid. Backed by top-tier investors, they’re building technology that supports real-time energy trading and optimisation at scale. They’re looking for a Data Scientist with strong experience in time-series forecasting to design, build, and deploy real-time models that directly impact trading decisions. You’ll be working with complex, high-variance datasets and collaborating closely with traders, engineers, and product teams to turn data into live insights that drive performance in fast-moving energy markets. Key Responsibilities:<ul><li>Develop and refine time-series forecasting models for energy trading and optimisation</li><li>Work with real-time, high-volume data streams to deliver actionable insights</li><li>Partner with traders, data scientists, and product engineers on live trading strategies</li><li>Build and deploy production-ready ML models that power operational decision-making</li><li>Continuously improve model accuracy, speed, and scalability</li></ul> What They’re Looking For:<ul><li>Strong background in data science, statistics, or applied mathematics (advanced degree preferred)</li><li>Proven experience with time-series forecasting and real-time data environments</li><li>Skilled in Python and familiar with cloud-based tools such as GCP and Docker</li><li>Strong analytical and problem-solving skills with a commercial mindset</li><li>Interest in climate tech and a desire to apply data science to sustainability challenges</li></ul> Tech Stack: Python, GCP, Docker, Streamlit, Figma (for internal tools) Why Join:<ul><li>Tackle complex, high-impact forecasting challenges in the energy sector</li><li>Work alongside a world-class team of scientists, traders, and engineers</li><li>Competitive salary and meaningful equity in a high-growth startup</li><li>Be part of a mission-driven company making a measurable impact on decarbonisation</li></ul> If you’re a high-performing data scientist with a passion for real-time systems and the energy transition, this is an opportunity to apply your skills to one of the most important challenges of our time.

Want to put your job search on autopilot? Join our platform, complete a 6-minute AI screening interview, and get auto-applied to 100s of high-paying roles.Sign up now at https://app.calyptus.co/auth/candidate/sign-up and let the opportunities come to you.____________________________________________________________Our stack<ul><li>Google Cloud Platform</li><li>Data Storage: GS, PostgreSQL (CloudSQL), BQ, ClickHouse</li><li>Language: Python</li><li>Tools: Airflow, k8s, Docker, FastAPI, gRPC, celery, NumPy, Pandas, SciPy</li><li>LLM APIs: OpenAI, Google, Anthropic, Perplexity</li><li> </li></ul>Examples of our projects<ul><li>Keyword search volumes: A metric showing how many times people search for a specific keyword in search engines.</li><li>Personal keyword difficulty: A personalized evaluation of how difficult it is to promote a specific domain for a particular keyword.</li><li>Keyword search intent: The goals users pursue when making a request in a search engine.</li><li>Brand performance: An evaluation of how often LLMs mention a brand in their responses.</li><li>Authority score: An indicator of both the quantity and quality of a backlink profile.</li></ul> Who we are looking for <ul><li>3+ years of experience as a DS or MLE</li><li>Knowledge of Natural Language Processing (NLP) techniques (TF-IDF, BERT, FastText)</li><li>Strong understanding of machine learning algorithms, probability theory, statistics, and linear algebra</li><li>High proficiency in Python and the ML stack</li><li>Hands-on experience with LLMs</li><li>Knowledge of SQL</li></ul> Not required, but a plus<ul><li>Practical knowledge of RAG and building AI agents</li><li>Experience deploying and maintaining LLM-based solutions in production</li><li>Experience with GCP and Vertex AI</li><li>Experience developing ETL processes with Airflow</li><li>You share our common values: Trust, because we prefer to speak up and be our true selves; Sense of Ownership, because it’s not worth wasting time on something you don’t believe in; and enthusiasm for Constant Changes, because we are always looking to make things better</li></ul> ____________________________________________________________Want to put your job search on autopilot? Join our platform, complete a 6-minute AI screening interview, and get auto-applied to 100s of high-paying roles.Sign up now at https://app.calyptus.co/auth/candidate/sign-up and let the opportunities come to you.

Job SummaryWe are seeking a talented and driven Data Scientist with Secret Clearance to join our dynamic team. In this role, you will apply advanced data analytics and machine learning techniques to solve complex problems in a variety of domains. You will work with large datasets, develop predictive models, and support decision-making processes while adhering to the highest standards of security and confidentiality.As with any position, additional expectations exist. Some of these are, but are not limited to, adhering to normal working hours, meeting deadlines, following company policies as outlined by the Employee Handbook, communicating regularly with assigned supervisor(s), and staying focused on the assigned tasks including company meetings, and completing other tasks as assigned.Responsibilities<ul type="disc"><li>Analyze large and complex datasets to extract actionable insights that will inform business strategies and decisions</li><li>Develop, implement, and maintain predictive models and machine learning algorithms</li><li>Collaborate with cross-functional teams to understand business needs and translate them into technical solutions</li><li>Use statistical methods, data mining, and machine learning to uncover trends and patterns within the data</li><li>Prepare reports and presentations that effectively communicate your findings to both technical and non-technical stakeholders</li><li>Ensure compliance with all security protocols and confidentiality requirements, adhering to industry standards and internal policies</li><li>Support senior leadership in strategic decision-making through advanced data-driven insights</li><li>Stay up-to-date with the latest developments in data science, machine learning, and related fields</li><li>Provide technical guidance and mentorship to junior data scientists and analysts</li></ul>Basic Qualifications<ul type="disc"><li>US Citizenship Required</li><li>Active Secret Security Clearance</li><li>If applicable: If you are or have been recently employed by the U.S. government, a post-employment ethics letter will be required if employment with VSolvit is offered</li><li>Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related field (Master's preferred)</li><li>At least 3+ years of experience as a Data Scientist or in a related data analysis role</li><li>Strong proficiency in Python, R, or similar programming languages for data analysis</li><li>Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)</li><li>Strong knowledge of SQL and experience with relational databases</li><li>Familiarity with data visualization tools like Tableau, Power BI, or similar</li><li>Solid understanding of statistical modeling, hypothesis testing, and data-driven decision-making</li><li>Excellent communication skills, with the ability to present technical findings to non-technical stakeholder</li><li>If applicable: If you are or have been recently employed by the U.S. government, a post-employment ethics letter will be required if employment with VSolvit is offered</li></ul>Preferred Qualifications<ul type="disc"><li>Experience working with classified government data or in a defense-related environment</li><li>Familiarity with cloud platforms (AWS, Azure, etc.) and data processing tools</li><li>Knowledge of big data technologies (e.g., Hadoop, Spark)</li><li>Experience with DevOps practices and version control (Git, GitHub)</li><li>Strong problem-solving skills and ability to work in a fast-paced environment</li><li>Machine Learning experience is a plus</li></ul>Company SummaryJoin the VSolvit Team! Founded in 2006, VSolvit (pronounced 'We Solve It') is a technology services provider that specializes in cybersecurity, cloud computing, geographic information systems (GIS), business intelligence (BI) systems, data warehousing, engineering services, and custom database and application development. VSolvit is an award winning WOSB, CA CDB, MBE, WBE, and CMMI Level 3 certified company. We offer a customizable health benefits program that best meets the needs of its employees. Offering may include: medical, dental, and vision insurance, life insurance, long and short-term disability and other insurance products, Health Savings Account, Flexible Spending Account, 401K Retirement Plan options, Tuition Reimbursement, and assorted voluntary benefits. Our goal is to grow together and enjoy the work that we do as a team.VSolvit LLC is an Equal Opportunity/Affirmative Action employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status.PDN-a06bae9a-607a-4464-ae69-53a79e2690f1

<div><h2>Capital Markets Data Scientist</h2>PayPal's Capital Markets Data Scientist role is a Senior Manager level that offers a unique opportunity to work with global loan data encompassing diverse portfolios to deliver actionable analytics. This role supports internal teams and investors by providing sophisticated data insights and analytics for financial modeling, with a focus on Asset-Backed Securities (ABS) deals in collaboration with counterparties. This position is vital to driving data-informed decisions that facilitate PayPal's leadership in innovative financial products within global capital markets.Essential Responsibilities:<ul><li>Develop and articulate clear objectives and implement strategies that deliver results and meet Financial goals</li><li>Influence decision-making at the senior leadership level</li><li>Perform the most highly complex credit and lending assessments using knowledge and extensive business expertise</li><li>Develop and deliver innovative strategies that benefit customers and/or clients for financial success</li><li>Lead major business projects which impact a business unit or entire function</li><li>Design, evaluate, and select financial objectives based on thorough understanding of business needs and industry trends</li><li>Lead others to solve issues of diverse scope</li></ul>Expected Qualifications:<ul><li>Minimum of 12 years of relevant work experience and a Bachelor's degree or equivalent experience.</li></ul>Data Scientist Responsibilities:<ul><li>Analyze and aggregate PayPal's global loan data to provide comprehensive insights for internal stakeholders and investor reporting.</li><li>Deliver analytics-driven support for financial model building, including cash flow analysis, credit risk assessment, and pricing strategies.</li><li>Lead efforts in creating dashboards, reports, and presentation materials that communicate complex data and trends to executive leadership and investors.</li><li>Enhance data pipelines and infrastructure to ensure scalable, accurate, and secure handling of high-volume, complex loan-level datasets.</li><li>Develop, validate, and maintain robust financial and credit models used for ABS transaction structuring and portfolio monitoring.</li><li>Collaborate closely with ABS counterparties, investment teams, and business units to provide timely analytics for deal execution and capital markets activities.</li><li>Stay updated and implement industry best practices around structured finance analytics, data privacy, and regulatory compliance.</li><li>Liaise with many cross functional teams on everything related to capital markets workstreams.</li></ul>Minimum Qualifications:<ul><li>Minimum of 5 years of relevant experience, including extensive exposure to data and loan portfolio analytics</li><li>Bachelor's degree in Finance, Economics, Mathematics, Statistics, Data Science, or related quantitative field; advanced degree preferred</li></ul>Preferred Qualifications:Education:<ul><li>Bachelor's or Master's degree or higher in quantitative disciplines such as Mathematics, Statistics, Economics, Finance, Business Analytics, Engineering, or Data Science from accredited institutions.</li></ul>Professional Experience & Skills:<ul><li>5+ years of experience in data analytics, structured finance, or credit risk management, preferably at a fintech company, investment bank, or hedge fund.</li><li>Proven track record working with large-scale loan data across multiple asset classes, including ABS portfolios.</li><li>Strong experience building and maintaining financial and credit risk models that support investment decisions and capital markets transactions.</li><li>Proficiency in data management and analytics tools including SQL, Python, R, Tableau, Excel, and PowerPoint.</li><li>Skilled in synthesizing complex datasets to derive meaningful insights with urgency and accuracy.</li><li>Excellent project management skills, including the ability to drive results and influence cross-functional partners.</li><li>Experience advising internal stakeholders and external investors with clear, compelling communication of analytical results.</li><li>Demonstrated leadership in team development and mentorship, fostering high productivity and continuous learning.</li></ul>Work Permit and Relocation Prerequisites:<ul><li>Candidates must possess valid authorization to work in the country where the position is located.</li><li>Relocation assistance is not provided for this role.</li></ul>PayPal is committed to fair and equitable compensation practices.Actual Compensation is based on various factors including but not limited to work location, and relevant skills and experience.The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits.The US national annual pay range for this role is $137,500 to $236,500PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit PayPal's official contact page.For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important assetyou. That's why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit PayPal's benefits page.PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.Notice to Applicants and Employees who reside within New York City. Click here to view the notice.</div>

White Collar Factory (95009), United Kingdom, London, London Data Scientist - Deep Learning Practitioner About This Role Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to derive insights from complex data, working in close collaboration with our business partners. This role will primarily focus on developing proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using Large Language Models. What you’ll do <ul><li>Develop new deep learning approaches to advance our current underwriting models, which form the heart of our lending business.</li><li>Apply these to new types of (multi-modal) data in order to stay at the forefront of innovation.</li><li>Provide consultancy to our tech and product partners, to help design, develop and launch products powered by Large Language Models (LLMs). This collaboration will help provide seamless experiences for our customers and associates.</li><li>Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions.</li><li>Work cross-functionally on projects that support key business initiatives and drive sustainable growth. </li></ul>What we’re looking for <ul><li>Experience developing and deploying deep learning models, particularly for sequential data (e.g. time series, language) using techniques such as LSTMs or transformers.</li><li>Hands-on experience with modern Machine/Deep Learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.</li><li>Familiarity with both pre-training and fine-tuning of large-scale models.</li><li>Experience working with structured and unstructured data, such as text, logs, or time series and tokenisation techniques.</li><li>A strong understanding of probability, statistics, machine learning and familiarity with large data set manipulation.</li><li>Experience in producing reliable and maintainable code in Python, with an ability to adapt to new languages and technologies.</li><li>Ability to communicate findings to a diverse business focused audience, influencing others in both verbal and written form.</li><li>A drive for continued learning through an internal and external focus, in order to develop enterprise and industry leading solutions. </li></ul>We are committed to creating a level playing field and seek to create teams that are representative of our customers and the communities we serve. We’d love to hear from you if you identify with a typically under-represented group in our industry and are particularly keen to hear from women, the LGBTQ+ community and ethnic minority candidates. Where and how you'll work This is a permanent position based in our Nottingham or London office. We have a hybrid working model, so you’ll be based in our office 3 days a week on Tuesdays, Wednesdays and Thursdays, and can work from home on Monday and Friday. Many of our associates have flexible working arrangements, and we're open to talking about an arrangement that works for you. What’s in it for you <ul><li>Bring us all this - and you’ll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation</li><li>We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers)</li><li>Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance – with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave</li><li>Open-plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms. In London, you can heighten your mood with a run on our rooftop running track or an espresso at the Workshop Coffee café </li></ul>What You Should Know About How We Recruit We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it’s about what you do, not just what you say. That’s why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages. We Also Partner With Organisations Including The Women In Finance And Race At Work Charters, Stonewall And UpReach To Find People From Every Walk Of Life And Help Them Thrive With Us. We Have a Whole Host Of Internal Networks And Support Groups You Could Be Involved In, To Name a Few <ul><li>REACH – Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies</li><li>OutFront – to provide LGBTQ+ support for all associates</li><li>Mind Your Mind – signposting support and promoting positive mental wellbeing for all</li><li>Women in Tech – promoting an inclusive environment in tech</li><li>EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry </li></ul>Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Job Description:Principal Associate, Data Scientist - US Card Upmarket Acquisition Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description The US Card Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions and management of new and existing credit card customers. We collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies -- Python, Conda, AWS, H2O, Spark, and more -- to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models, from idea to implementation. This includes designing and executing experiments, developing and iterating on machine learning models, and deploying production-ready solutions that directly impact business outcomes. Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing and deploying production-ready data science solutions using open-source tools and cloud computing platforms. Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. A data guru. Big data doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: Currently has, or is in the process of obtaining a Bachelor's Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date At least 1 years' experience in open source programming languages for large scale data analysis At least 1 years' experience with machine learning At least 1 years' experience with relational databases Preferred Qualifications: Master's Degree in STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in STEM field (Science, Technology, Engineering, or Mathematics) At least 1 year of experience working with AWS At least 3 years' experience in Python, Scala, or R for large scale data analysis At least 3 years' experience with machine learning At least 3 years' experience with SQL Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $144,200 - $164,600 for Princ Associate, Data Science McLean, VA: $158,600 - $181,000 for Princ Associate, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Title: Senior Data Scientist Job Location: Salford Quays, Manchester Job Type: Permanent, Full-time Job ID: SF18973 Naimuri is offering the chance to help make the UK a safer place through innovation. We partner with government and law enforcement on some of the most challenging data and technology problems out there, and we're looking for a Senior Data Scientist to join our mission. We strongly encourage candidates of all different backgrounds and identities to apply. We are committed to building an inclusive, safe and supportive environment that allows everyone to do their best work. We are happy to support any accessibility or neurodiversity requirements that you may need during the recruitment process. About us: We’ve been around for about ten years and grown from being a little-known tech start-up to creating our own community at the heart of Manchester’s thriving tech ecosystem. The name Naimuri is Japanese and simply means… ‘nai’ meaning ‘not’‘muri’ meaning ‘overburden’ This principle guides everything we do, from our technology and processes to our people and culture. We empower our teams to do what they think is right, giving them the confidence to explore new ways of working and deliver the finest solutions in an agile, bias-free environment. Our business is focused on 4 cornerstones: Wellbeing, Empowerment, Perpetual Edge and Delivery. People and culture are at the heart of Naimuri, so that collectively, we can realise our mission of ‘making the UK a safer place to be’. About the team: The Data capability team at Naimuri offers a unique opportunity to apply your skills to impactful projects. It's a rapidly growing, collaborative, and supportive environment where we analyse and investigate data, design solutions to exciting data-driven challenges, and make a real difference for our customers. We are passionate about continuous learning and fostering shared expertise within the team. Data Scientists within our Data capability team are often working on: <ul><li>Analysing customer requirements in long-term projects and new bid work to uncover opportunities for customers to leverage their data.</li><li>Analysing and modelling customer data, performing statistical analyses, designing cleansing, transformation and normalisation processes, performing feature extraction/reduction, and designing solutions and opportunities.</li><li>Performing, visualising, and presenting data analyses and analytics to customers and project leads, including on-site.</li><li>Engineering platforms, databases, and data pipelines as part of broader delivery solutions.</li><li>Training (inc. transfer learning and feature extraction) and deploying ML/AI models for prediction, detection, classification, etc.</li><li>Writing or supporting software solutions that implement data science models, tools, and techniques.</li></ul> About the role: As a Senior Data Scientist, you will help maintain our strong reputation for delivering robust solutions by taking a conscientious and scientific approach to customer data. You will use your strong problem-solving skills to design and develop innovative techniques and tools in an agile manner. Working collaboratively with other data scientists, engineers, and developers, you will research, experiment, analyse and visualise complex data, presenting your findings to customers and colleagues. A key part of this role is mentoring and supporting earlier-career colleagues, helping to foster a culture of continuous learning and shared expertise across the team. You will work closely with customers, other data scientists, data architects, data engineers, software developers, and testers to: <ul><li>Investigate, transform (with provenance), and model customer data, and potentially create synthetic data in lieu.</li><li>Apply statistical methods to analyse customer data and be able to report that analysis to co-workers, customers, and project leads.</li><li>Identify opportunities to apply, design and build algorithms to transform and interrogate data.</li><li>Visualise and communicate data and model and algorithm outputs for audiences of different levels of understanding.</li><li>Use data science techniques, including ML/AI, to design and build solutions to customer problems, and work with software developers, data engineers and testers to implement and assure them.</li><li>Work with data engineers and platform engineers to design, implement and test data ingest pipelines.</li><li>Work with other data scientists and ML and platform engineers to design, train, test and deploy ML/AI models.</li><li>Test and compare the effectiveness of different mathematical and computational techniques for working with data.</li><li>Conduct research into the application or development of new data science techniques, potentially collaborating with our expansive academic network, and co-supervising Masters and PhD candidates.</li><li>Experiment design and execution/running, and communication of the experiment plan.</li></ul> About you We're looking for someone who: <ul><li>Has significant industry experience as a data scientist and is passionate about data, with opinions on the best ways of working, techniques, and tooling.</li><li>Has experience leading a team or project and wants to help others develop and learn.</li><li>Takes a conscientious, curious, and scientific approach to their work.</li><li>Continually learning about state-of-the-art techniques in technology, academic, and industry articles.</li><li>Possesses strong analytical problem-solving abilities to design and develop innovative data science solutions.</li><li>Can communicate and present complex ideas and findings to diverse audiences, including customers, executives, and non-specialists.</li><li>Has performed deep dives into data and presented the results of analysis and modelling using tools like Jupyter Notebooks.</li><li>Has experience designing and developing data ingestion and transformation pipelines in languages like Python, potentially using cloud solutions in AWS, Azure, or GCP.</li><li>Is familiar with the full lifecycle of ML/AI models, including collating training data, design, training, evaluation, and deploying automated pipelines.</li><li>Has experience helping to transform or implement an organisation's data science strategy.</li><li>Is comfortable designing and executing experiment plans and communicating them to stakeholders.</li></ul> Nice to haves: Experience with any of the following specialisms: Data Synthesis, Test and Evaluation, AI Assurance, Knowledge Graphs and Ontologies, Data Governance and Compliance, or Deepfake Detection.Creating Python-based applications and/or APIs.A degree in a field like data science, physics, computational science, mathematics, or statistics (though we value demonstrable experience just as much!). Location: Our Head Office is based in Salford Quays, Manchester, with satellite teams currently in London and Gloucestershire. We offer hybrid working where you can work from home for part of your working week with time on site being based on the needs of your assigned delivery and agreed Ways of Working for your team. This would normally be a maximum of one or two days per week but you would be welcome to spend more days in the office if you preferred. Pay and benefits: Naimuri pays competitively within the industry based on your role's base location rates. The salary for this position is dependent upon your experience. We assess seniority relative to the team at Naimuri during the interviewing process. A full time working week is 37.5 hours and you have flexibility over when you give that time. We also offer part-time working which can be discussed during the recruitment process. Our core hours are 10:00am - 3:00pm and our office hours are between 7:30 and 18:00 Monday to Friday. Benefits include: ● Flexible/Hybrid working options● A company performance related bonus● Pension matched 1.5x up to 10.5%● AXA group 1 medical cover● Personal training budget● Holiday buy-back scheme● A flexible benefits scheme Recruitment Process: We want to ensure that you feel comfortable and confident when interviewing with us. To help you prepare, our recruitment team will discuss the process in more detail with you when you apply. We are happy to support any accessibility or neurodiversity requirements.

Estamos ampliando nuestra Factoría de IA y buscamos un/a Data Scientist con experiencia en Google Cloud para desarrollar modelos con impacto real en negocio, trabajando con una arquitectura moderna basada en BigQuery, Dataflow, Pub/Sub y Vertex AI. Colaborarás con ML Engineering para llevar modelos a producción y exponerlos como servicios. Tu misión<ul><li>Convertir problemas de negocio en modelos medibles y útiles.</li><li>Asegurar reproducibilidad, trazabilidad y calidad desde los datos hasta los resultados.</li><li>Colaborar para que los modelos lleguen a producción con garantías.</li></ul> Tecnología con la que trabajarás<ul><li>Datos: BigQuery (modelado, optimización y control de costes), Dataflow/Pub/Sub para pipelines y Feature Store para features consistentes.</li><li>Modelos: Vertex AI (Workbench, Experiments, Pipelines, Model Registry, Endpoints/Batch) para entrenar, registrar y servir modelos.</li><li>Exposición: Integración con Cloud Run + API Gateway junto al equipo de ML Engineering.</li><li>Observabilidad y negocio: Métricas y cuadros de mando en Looker.</li><li>Gobierno: CI/CD, IaC y prácticas alineadas a GDPR/EU AI Act.</li></ul> Lo que harás<ul><li>Analizar datos en BigQuery, definir KPIs y criterios de éxito.</li><li>Diseñar datasets y features reutilizables con Feature Store.</li><li>Entrenar y comparar modelos en Vertex AI; ajustar hiperparámetros y validar resultados.</li><li>Evaluar calidad técnica (ej. ROC-AUC, F1, RMSE) y valor de negocio (€).</li><li>Explicar modelos con técnicas interpretables (SHAP, ICE, PDP).</li><li>Colaborar en umbrales, AB testing y pilotos con negocio.</li><li>Empaquetar entrenamientos en Pipelines y registrar artefactos en Model Registry.</li><li>Definir métricas operativas y políticas de reentrenamiento.</li><li>Documentar con model cards, fichas de datasets y notebooks claros.</li></ul> Requisitos imprescindibles<ul><li>5–8+ años en Data Science con modelos reales en producción.</li><li>Fuerte base en estadística y machine learning.</li><li>Dominio de Python (pandas, scikit-learn; TF/PyTorch valorables) y SQL avanzado.</li><li>Experiencia en BigQuery y optimización de costes.</li><li>Trabajo real con Vertex AI (Workbench, Experiments, Pipelines, Model Registry).</li><li>Conocimiento de Feature Store y ciclos train/serve.</li><li>Colaboración con ML Engineering para despliegues en Endpoints/Batch y definición de SLOs.</li><li>Buenas prácticas de datos, gobierno y cumplimiento (GDPR / EU AI Act).</li><li>Conocimiento de Git y habilidades de comunicación orientadas a producto.</li></ul> Te esperamos! ????

It's an exciting time in our Pricing and Analytics department here at AXA UK. Our transformation programme has recently been relaunched, aligned to AXA Retail's new Pricing and Analytics strategy. We're investing a lot in growing our department in size and capability across our IT systems, analytical toolset and learning and development. AXA are investing a lot in growing our department in size and capability across our IT systems, analytical toolset and learning and development. We'd love to hear from motivated people who can help us deliver our commitments to our business, our customers, and our people. Within AXA Retail we’re looking for a Senior Data Scientist. You’ll support initiatives that leverage internal data assets and innovative techniques to develop features and insights that enhance pricing models and strategic decision-making. You’ll be involved in exploring, experimenting with, and optimizing internal data to generate high-value features that improve model performance and business outcomes. At AXA we work smart, empowering our people to balance their time between home and the office in a way that works best for them, their team and our customers. You'll work at least two days a week (40%) away from home, moving to three days a week (60%) in the future. Away from home means either attendance at one of our office locations, visiting clients or attending industry events. We’re also happy to consider flexible working arrangements, which you can discuss with Talent Acquisition. What you’ll be doing: <ul><li>Assist in Identify and develop innovative features and insights from internal data sources to enhance business value.</li><li>Support the design, testing, and refinement of features derived from internal data.</li><li>Collaborate with data engineering teams to operationalize features within scalable production environments.</li><li>Maintain a good understanding of internal data assets, ensuring quality, consistency, and accessibility.</li><li>Contribute to strategies for data cataloguing, lineage, and documentation to support exploration and reuse.</li><li>Work with IT and data platform teams to help develop scalable, robust data pipelines.</li><li>Support the application of advanced analytical techniques (spatial analysis, text mining, interaction features) to uncover hidden value.</li><li>Partner with pricing, underwriting, claims, and fraud teams to understand data needs and communicate findings. </li></ul>Due to the number of applications we expect to receive for this role, we reserve the right to close this advert earlier than the listed closing date to ensure we’re able to effectively manage interest. Therefore, if you’re interested in joining us at AXA, please don’t hesitate to apply. What you’ll bring: <ul><li>Strong statistical modelling, data manipulation and financial analysis skills</li><li>Proficient in open-source predictive analytics software such as R and Python for advanced data analysis.</li><li>Ability to work effectively under pressure, meet strict deadlines, and maintain high levels of accuracy and reliability.</li><li>Proven ability to plan and prioritise own work. Ability to work under pressure and to strict deadlines whilst maintaining reliability and accuracy.</li><li>Excellent numerical and mathematical skills, with a degree in a related discipline or equivalent proficiency.</li><li>Detailed understanding of appropriate statistical techniques for insurance risk analysis and demand pricing</li><li>Proven ability to plan and prioritise own work. Ability to work under pressure and to strict deadlines whilst maintaining reliability and accuracy</li><li>Ability to grasp the significance and meaning of a range of technical and complex issues relating to underwriting, claims handling, pricing, reserving and financial analysis of insurance. </li></ul>As a precondition of employment for this role, you must be eligible and authorised to work in the United Kingdom. What we offer: At AXA UK, we’re appreciative of the people who work for us and our rewards package is reviewed regularly to reflect that. You can expect to receive: <ul><li>Competitive annual salary dependent on experience</li><li>Annual company & performance-based bonus</li><li>Contributory pension scheme (up to 12% employer contributions)</li><li>Life Assurance (up to 10 x annual salary)</li><li>Private medical cover </li><li>25 days annual leave plus Bank Holidays</li><li>Opportunity to buy up to 5 extra days leave or sell up to 5 days leave</li><li>Wellbeing services & resources </li><li>AXA employee discounts </li></ul>To apply, click on the ‘apply for this job’ button, you’ll then need to log in or create a profile to submit your CV. We’re proud to be an Equal Opportunities Employer and don’t discriminate against employees or potential employees based on protected characteristics. If you have a long-term condition or disability and require adjustments during the application or interview process, we’re proud to offer access to the AXA Accessibility Concierge. For our support, please send an email to martin.eels@axa-uk.co.uk. Who we are: AXA Retail helps people live the life they love, knowing we’ve got their back, at home and on the road. Our people are vital to us becoming more digital, faster and easier to access. We’re a dynamic team of experts completely committed to making sure our customers ‘get back to the good stuff’ when the unexpected happens.

Vind jij het te gek om met de laatste techniek en AI tooling een concrete oplossing te bouwen die de diensten voor klanten beter, sneller en gemakkelijker maken? Dan is dit de baan voor jou! We breiden ons data science gilde uit en zijn op zoek naar een collega die ons centrale AI team binnen Schade & Inkomen komt versterken. Je maakt deel uit van het centrale Pricing & Data Office. Het Pricing & Data Office denkt mee met de business, zoekt actief de samenwerking en is altijd op zoek naar duurzame en werkende oplossingen. Verbinding met de business, inhoudelijke expertise, verantwoordelijkheid, resultaatgerichtheid en “fun” zijn voor het Pricing & Data Office belangrijk. Het is een team van gepassioneerde specialisten. Wat je gaat doen Binnen het Data Office hebben we een team dat verantwoordelijk is voor het bouwen van impactvolle AI oplossingen. Met deze AI oplossingen helpen we Schade & Inkomen om belangrijke processen te digitaliseren. Een voorbeeld hiervan is het digitaliseren van onze Claims processen. Je belangrijkste doel is om samen met je collega’s data science-oplossingen te creëren voor operationele teams zoals Acceptatie en Claims. Je hebt hierbij ook veel contact met de collega’s voor wie je de oplossingen bouwt. We maken dus veel impact! Je begrijpt hoe je collega’s uit de business kan helpen hun wensen te vertalen naar AI oplossingen, en vindt het bovenal leuk om jouw oplossingen te presenteren voor de business en hen te helpen met de adoptie van AI. Je krijgt eigenaarschap over en wordt verantwoordelijkheid voor end-to-end oplossingen; van het definiëren van requirements tot het in productie brengen van de oplossing. Met jouw oplossingsgerichte en proactieve mindset ontwerp je samen met je team wat de beste data science oplossing voor problemen uit de business, en je realiseert deze met behulp van onze AI toolkit. We werken agile met collega’s uit de business aan projecten die veelal sprint-overstijgend zijn. Concreet breng je AI-oplossingen naar productie zodat je oplossingen echt waarde creëren voor ons bedrijf van morgen. Het onderzoeken en toepassen van nieuwe technologie speelt een belangrijke rol. Je maakt gebruik van state-of-the-art technieken zoals AI as a service en LLMs, zoals Cognitive Services en OpenAI. Daarnaast prioriteer en bewaak je de voortgang van projecten. Daarnaast draag je actief bij aan innovatie binnen NN. Tijdens onze maandelijkse innovatiedag onderzoek je samen met je collega’s welke nieuwe technieken toepasbaar zijn binnen ons bedrijf. Duik jij graag in de laatste AI trends om oplossingen voor business problemen te vinden, dan is deze baan iets voor jou. Wat wij jou bieden NN investeert in een inclusieve, inspirerende werkomgeving en in vaardigheden en competenties voor de toekomst. Daarbij passen <a>arbeidsvoorwaarden</a> die aansluiten bij wat er vandaag nodig is én die rekening houden met de toekomst. Zo bieden we onze medewerkers de mogelijkheid het beste uit zichzelf te halen. Wij bieden jou: <ul><li>Salaris tussen de € 5.363.- en € 7.661.- per maand (obv een 40-urige werkweek) afhankelijk van jouw kennis en ervaring. Het is ook mogelijk 36 of 38 uur per week te werken</li><li>13de maand en vakantiegeld, maandelijks uitbetaald bij je salaris</li><li>27 vakantiedagen bij een werkweek van 5 dagen en één Diversiteitsdag</li><li>Een moderne pensioenregeling uitgevoerd door BeFrank</li><li>Volop training- en opleidingsmogelijkheden</li><li>NS Business Card 2e klas, waarmee je onbeperkt kunt reizen, ook privé. Reis je liever met eigen vervoer? Declareer dan je kilometers</li><li>Thuiswerkvergoedingen voor internet en een goede werkplek </li></ul>Wat je meebrengt Jij ben resultaatgericht en vindt het mooi code projecten op te leveren voor de business, maar ziet vooral waarde in de verdere adoptie van onze AI oplossingen. Je open houding en sterke communicatieve skills helpen hier enorm bij. Verder heb je: <ul><li>Een afgeronde wo-opleiding met een master in in Computer Science, Econometrie, Wiskunde of een andere STEM-gerelateerde studie / minimaal 5 jaar ervaring opgedaan in het ontwikkelen van ML-applicaties in Python</li><li>Praktische kennis van het data science-proces, zoals dataverzameling, opschoning, modelbeoordeling en modelimplementatie</li><li>Evaring met het ontwikkelen van geautomatiseerde API’s en cloud-oplossingen met behulp van (Azure) CI/CD-tools, Git, Terraform</li><li>Ervaring met het ontwerpen van Generatieve AI oplossingen zoals LLMs etc. om zo o.b.v business requirements zelfstandig en pro actief advies te kunnen geven hoe AI in te zetten op uitdagende business vraagstukken</li><li>De vaardigheden om relaties op te bouwen met een breed stakeholder veld, buiten het programma (operations medewerkers, proces experts etc.)</li><li>Bewezen ervaring in het zelfstandig opzetten van complexe AI ‘end-to-end’ oplossingen die directe impact hebben geleverd</li><li>Ervaring met het coachen van andere Data scientist op de inhoudelijke Data Science kennis</li><li>Een goede beheersing van de Nederlandse taal is een vereiste </li></ul>Met wie je werkt Het team waar je op dagdagelijkse basis mee samen werkt bestaat uit een groep data scientists, een 2-tal engineers die het team helpen om het werk in productie te zetten en een programma manager die onze werkzaamheden kadert. Uiteraard werk je met veel collega’s uit de business. Samen met deze collega’s werken wij dagelijks met veel enthousiasme en toewijding aan het optimaliseren en innoveren van de klantbediening, processen en kwaliteit, in nauwe samenwerking met de operationele teams. Daarnaast ben je lid van het data science gilde waarin ongeveer 40 data scientists elkaar ontmoeten. Hier wissel je kennis en ervaringen uit met vakgenoten. Wij geloven dat elke data scientist iets kan leren van vakgenoten en andersom ook iets kan leren aan anderen in de community. Op die manier breng je jouw carrière in een stroomversnelling en leveren we maximale waarde met onze AI oplossingen. Heb je vragen? Bel of stel je vraag via WhatsApp aan Chris Bartels, Programma manager Pricing & Data Office via 06-11271619 over de functie. Voor vragen over de procedure kun je terecht bij Joost Stroes, TA Specialist via joost.stroes1@nn-group.com. Twijfel jij of je wel 100% aan de criteria voldoet? Dan willen we je aanmoedigen om toch te solliciteren. Wij zijn benieuwd naar jouw unieke kwaliteiten! We bieden je <ul><li>NS Business card, ook privé te gebruiken</li><li>27 vakantiedagen en 1 Diversiteitsdag</li><li>13e maand en vakantiegeld</li><li>Hybride werken</li></ul>

Question	Topic	Difficulty	Ask Chance
Bootstrapping Confidence Intervals	Statistics	Easy	Very High
Lyft Ops Dashboard	Data Visualization & Dashboarding	Medium	Very High
Split Data Without Pandas	Python & General Programming	Medium	Very High

Swiggy Data Scientist Interview Questions + Guide in 2025

Overview

Swiggy Data Scientist Interview Process

Swiggy Data Scientist Interview Questions

Swiggy Data Scientist Jobs