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

Myntra Data Scientist Interview Guide

Getting ready for an Data Scientist interview at Myntra? The Myntra Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for Myntra Data Scientist roles.</li>
<li>Gain insights into the Data Scientist interview process at Myntra.</li>
<li>Practice real Myntra 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 Myntra Data Scientist interview.


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

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

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

Myntra 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

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

Myntra Data Scientist Interview Questions

hackajob is collaborating with Bupa to connect them with exceptional tech professionals for this role. Data Scientist (Fixed Term Contract) Hybrid working options- ideally 1-2 days per week in office Location: London EC2R 7HJ, Salford M50 3SP, Staines TW18 3DZ 12 Months Fixed Term Contract Salary range: up to £60K (depending on exp & location) Full time: scheduled 37.5 hours per week We make health happen At Bupa, we’re passionate about using technology to make a meaningful difference. With our colleagues, customers, patients, and residents at the heart of everything we do, you’ll have the opportunity to work on innovative, high-impact projects that span our entire organisation. As part of our ambitious 2027 strategy, you’ll join a growing Data Science team focused on implementing modern data science and MLOps standards while upholding ethical and responsible practices. You will work within a cross-functional team leveraging our new enterprise cloud infrastructure to design and develop products that drive both commercial value and improved customer outcomes. How you’ll help us make health happen Championing and delivering bespoke solutions to complex business problems to support commercial growth and enhance customer experiences and outcomes. Leading and supporting end-to-end data science projects, including business case development, solution design, feature engineering, model development, deployment, and MLOps. Taking ownership of existing ML/AI projects, including ongoing monitoring of model performance, data drift, scoring latency, and continuous optimisation. Acting as a data evangelist by educating stakeholders on the art of the possible, while actively sharing knowledge and collaborating with data scientists across Bupa’s global businesses. Working with multi-modal data sources (including structured, unstructured, and semi- structured formats such as electronic health records, clinical notes, imaging data) to extract insights, automate processes, and optimise pipelines through creatively applying AI methodologies. Committing to continuous professional development, aligning learning with organisational goals and emerging trends in AI and data science. Ensuring full compliance with regulatory frameworks and standards relevant to the health insurance sector (e.g., GDPR, DPA) as well as proactively aligning Bupa’s Responsible AI Framework. Key Skills / Qualifications Needed For This Role Applied experience in Data Science within a healthcare, clinical, insurance, or dental setting. Hands-on experience with SQL and Python, preferably within a cloud environment such as Snowflake, Azure and GCP. Demonstrated knowledge and experience in delivering end-to-end AI and GenAI projects, including business case development, model building, and deployment. A solid understanding of machine learning infrastructure and architecture, with the ability to support technical teams in developing scalable ML platforms. Strong communication skills, with the ability to present complex technical concepts to non-technical stakeholders. Experience working in an agile environment, preferably with familiarity using Azure DevOps tools such as Boards, Repos, and Pipelines to manage workflows and collaborate effectively. Benefits Our benefits are designed to make health happen for our people. Viva is our global wellbeing programme and includes all aspects of our health - from mental and physical, to financial, social and environmental wellbeing. We support flexible working and have a range of family friendly benefits. Joining Bupa in this role you will receive the following benefits and more: <ul><li> 25 days holiday per year, pro rata to your contract.</li><li> Access to a range of services to support your physical and mental wellbeing</li><li> Fixed term benefits allowance</li><li> Access to our confidential employee assistance programme</li><li> Workplace pension</li><li> Online discounts covering your everyday shopping, entertainment, eating out and more. </li></ul>Why Bupa? We’re a health insurer and provider. With no shareholders, our customers are our focus. Our people are all driven by the same purpose - helping people live longer, healthier, happier lives and making a better world. We make health happen by being brave, caring and responsible in everything we do. We encourage all of our people to “Be you at Bupa”, we champion diversity, and we understand the importance of our people representing the communities and customers we serve. That’s why we especially encourage applications from people with diverse backgrounds and experiences. Bupa is a Level 2 Disability Confident Employer. This means we aim to offer an interview/assessment to every disabled applicant who meets the minimum criteria for the role. We’ll make sure you are treated fairly and offer reasonable adjustments as part of our recruitment process to anyone that needs them.

We’re looking for three talented Principal Data Scientists and one Senior Data Scientist to join our supportive and forward-thinking Commercial Data team. Each role offers a unique opportunity to make a real impact and shape how we use data to create meaningful change across the business. You’ll join a team that values openness, curiosity, and innovation, where your voice is heard and your contributions make a difference. Here, you can grow, mentor others, explore new ideas and help us deliver smarter, more impactful solutions across the business. As a Senior Data Scientist in the Customer Contact team at <a>E.On</a> Next, you will play a crucial role in leveraging data to drive agent performance, operational efficiency, and customer experience. We are looking for someone who has experience of working in a matrix organisation and is excited to work in a cross-functional team to ensure our data platform and digital solutions fully support <a>E.On</a> Next’s operational performance and business objectives. Here’s a taste of what you’ll be doing:<ul><li>Partner with colleagues across functions, using a consultative and collaborative approach, to listen carefully and help them see what’s possible through data.</li><li>Translate complex business challenges into thoughtful, practical data products, unlocking the full potential of advanced analytics, machine learning, and AI.</li><li>Create metrics, reports and dashboards to share insights through clear, compelling storytelling that empowers senior stakeholders to make decisions with confidence.</li><li>Apply, and implement at scale, a wide range of methods from classical techniques like regression to neural networks and AI.</li><li>Manage your projects according to best practices in technology architecture and development processes.</li></ul> Are we the perfect match?<ul><li>Excellent communicator; able to explain complex results or technical concepts to non-technical audiences with clarity and empathy.</li><li>Strong business awareness with a thorough understanding of the relationship between contact operations and customer experience.</li><li>Experience working collaboratively with cross-functional teams and engaging stakeholders at all levels to deliver impactful solutions.</li><li>Advanced analytical skills with experience in applying a variety of data science, analytics, and operational research techniques at scale to address business challenges.</li><li>Minimum 4 years’ hands-on experience as a Data Scientist, with exposure to productionised models.</li><li>Proficiency in Python (production-level) and SQL; confident with modern ML/AI libraries such as scikit-learn, TensorFlow, or PyTorch.</li><li>Familiarity with MLOps frameworks, model deployment, and cloud-based platforms (Databricks, AWS, Azure).</li></ul> It would be great if you had:<ul><li>Experience in the retail energy sector.</li><li>Degree (BSc or MSc) in a quantitative or technical field (Statistics, Mathematics, Physics, Computer Science, Machine Learning).</li></ul>

YOUR ROLE <ol><li>We're looking for a Senior Data Scientist who can build and optimize our AI models that power our voice AI platform. You'll be the brain behind our technology, ensuring our AI can handle complex conversations while maintaining high accuracy and natural-sounding interactions. </li></ol> Your work will involve: <ul><li>● Own end-to-end model development – from requirement gathering and algorithm design to implementation and deployment, you'll shepherd ML features through their complete lifecycle. </li><li>● Build for conversational intelligence – develop models that can handle hundreds of thousands of conversations per day with high accuracy and natural language understanding. </li><li>● Innovate through research – stay current with cutting-edge NLP and speech technologies, read research papers, and implement state-of-the-art solutions that give us a competitive edge. </li><li>● Design ML pipelines – create robust, scalable machine learning infrastructure that can continuously improve from our growing conversation data. </li><li>● Optimize for performance – identify and resolve model bottlenecks to ensure our voice AI delivers natural, real-time conversations without comprehension issues. </li></ul> Why This Role Rocks <ul><li>● You'll have a front-row seat to building and optimizing cutting-edge AI models for voice intelligence. </li><li>● You'll get to work on natural language understanding, speech recognition, and conversational AI. </li><li>● You will be developing models that power conversations with some of India's biggest enterprises (Our voice AI technology is vetted by technical leaders at companies like Paytm). </li><li>● You'll have direct impact on model accuracy, performance, and the company's AI capabilities. </li><li>● You'll build mission-critical AI systems that enable hundreds of thousands of natural-sounding conversations daily. </li></ul> QUALIFICATIONS <ul><li>● What We're Looking For </li><li>● 5+ years experience in data science, machine learning, or related field </li><li>● Strong background in natural language processing (NLP) and conversational AI systems </li><li>● Experience with speech recognition and text-to-speech technologies </li><li>● Proficiency in Python and data science libraries (NumPy, Pandas, scikit-learn) </li><li>● Familiarity with deep learning frameworks (PyTorch, TensorFlow, Hugging Face) </li></ul>● AI & ML Skills <ul><li>○ Experience fine-tuning language models (LLMs) for specific domains or tasks </li><li>○ Expertise in analyzing conversational data at scale and extracting actionable insights </li><li>○ Knowledge of customer intelligence systems and experience building data-driven applications </li><li>○ Understanding of speech-to-text optimization and improving transcription accuracy </li></ul>● Data Engineering & Analytics <ul><li>○ Experience with large-scale data processing (handling hundreds of thousands of conversations) </li><li>○ Ability to design and implement data pipelines for continuous model improvement </li><li>○ Knowledge of feature engineering techniques for conversational data </li><li>○ Experience with A/B testing methodologies to evaluate model improvements </li><li>○ Familiarity with data visualization tools for presenting insights to stakeholders </li></ul>● Startup Mindset <ul><li>○ You've built and deployed ML models in production environments </li><li>○ Comfortable with fast-paced environment where you'll own critical data science decisions </li><li>○ Collaborative approach - you work well with engineering teams, product, and </li><li>founders </li><li>○ Growth-minded and excited about building customer intelligence systems </li><li>that scale </li></ul> SOUNDS LIKE YOU? <ul><li>● User-obsessed: Users come first, above all else. </li><li>● Communication: You over-communicate. You communicate clearly and precisely, both verbally and in writing, including explaining technical concepts. </li><li>● Timeliness: You respect timelines and communicate beforehand if there is a blocker </li><li>● Ownership: You proactively take initiative to find solutions and focus on what must be done to create success. </li><li>● Grit: You pursue challenging goals with passion and courage. </li><li>● Intellectual curiosity: You want to constantly push yourself out of your comfort zone to try and learn new things </li><li>● Entrepreneurial: You are empowered to take decisions and act on them, treating this startup as your own</li></ul>

【About Tencent】Tencent is a world-leading internet and technology company that develops innovative products and services to improve the quality of life of people around the world. Founded in 1998 with its headquarters in Shenzhen China, our guiding principle is to use technology for good.We are not only a major video game publisher in the world, we also produce other high-quality digital content, enriching interactive entertainment experiences for people around the globe. We offer a range of services such as cloud computing, advertising, FinTech, and other enterprise services to support our clients' digital transformation and business growth. 【About Level Infinite】Level Infinite is a global gaming brand dedicated to delivering high-quality and engaging interactive entertainment experiences to a worldwide audience, wherever and however they choose to play. It operates from bases in Amsterdam and Singapore with staff around the world.To learn more about Level Infinite, visit www.levelinfinite.com, and follow on Twitter,Facebook, Instagram and YouTube. Primary Duties & Responsibilities:1. Establish trusting relations with acquired game studios, create high impact business insights to address game studio challenges and drive value.2. Collaborate and work closely with 2nd party game studios and business stakeholders to deliver excellent outputs and provide insights to support key business decisions.3. Build data analysis methodology to serve a large number of new games in development by using data statistical analysis, data mining, modeling, experimental testing and other methods.4. Propose, design and implement new data models to exploit opportunities and improve the game experience and business growth.5. Participate in the design of game index system, game health analysis, game growth strategy traction, game play optimization through mathematical statistics.6. Apply statistical theory, interdisciplinary knowledge, and machine learning models to solve business problems. Who We Look For1. Master degree or above in computer science, data science, machine learning, statistics, applied mathematics and other relevant fields is preferred.2. Highly proficient in R/Python/SQL for data analysis and modeling, familiar with big data platforms such as Hadoop/Hive/Spark.3. Experience designing, analyzing and optimizing testing methods.4. Experience in predictive modeling and analysis over large datasets.5. Ability to work in an analytical and structured manner, meticulous and pragmatic, know how to balance short term and long term deliverables.6. Proven track record leading big data projects, using common big data technologies.7. Excellent communication and influencing skills.8. Ability to develop and maintain good relations and communicate with people at all hierarchical levels.9. Strong problem solving skills and team spirit.10. Ability to reconcile technical and business perspectives.Preferred qualification:1. Hands-on experience deploying, managing, and operating AI/ML workloads in a production environment.2. Hands-on experience developing, deploying, and maintaining AI agents in production environments.3. Past data science experience in gaming industry. Equal Employment Opportunity at TencentAs an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.

Data Scientist | SurePay Location: Hybrid from Utrecht | FinTech SaaS | Fraud & AML Discovery Team Help us stop fraud before it starts. At SurePay, we’ve processed over 10 billion IBAN-Name Checks keeping payments secure and fraud-free for over 200 banks and 300+ corporates across Europe. Now, we’re building a new generation of fraud and anti-money laundering (AML) products, and we’re looking for a hands-on Data Scientist to join our Discovery team. This is a high-impact, early-stage role. You’ll dive into real-world financial data, shape product ideas, and build working prototypes that lay the foundation for production-ready models. If you're excited by ambiguous challenges, curious about fraud detection, and want to apply your skills in a meaningful way, this might be the role for you. The opportunity As a Data Scientist at SurePay, you'll work at the intersection of statistics, machine learning, software engineering, and experimentation. You’ll join a small, sharp team building proof-of-concepts that test fraud signals, model behaviors, and anomaly detection techniques all with real-world data and a clear product vision.This isn’t a purely research-focused role. It’s exploratory, fast-paced, and practical. You’ll take ownership from idea to prototype. Designing models, validating them, and making sure they’re solving the right problems in the right way. What you’ll do<ul><li>Explore large financial datasets to uncover patterns, edge cases, and insights</li><li>Build quick-turnaround ML prototypes to validate hypotheses and identify signal quality</li><li>Select the right algorithms based on the problem (supervised, unsupervised, anomaly detection, etc.)</li><li>Fine-tune models with awareness of overfitting, false positives, and interpretability</li><li>Work closely with product and ML engineering to turn POCs into scalable systems</li><li>Help define how we measure success for fraud detection (e.g., recall vs. precision, AUC, business cost)</li><li>Champion model explainability and ethical ML practices</li><li>Contribute ideas, structure, and rigor to an early-stage product team</li></ul> What we’re looking forYou’re a Data Scientist who loves solving messy problems and working across the full stack of data science. You bring structure to chaos, prototype quickly, and care about solving real-world problems not just building cool models. Must-haves<ul><li>3–5 years of experience in Data Science roles, ideally within fraud, security, or high-noise domains</li><li>Strong statistical and analytical skills. You should be able to reason clearly about data and model performance</li><li>Proficient in Python and key ML libraries (e.g., pandas, scikit-learn, PyTorch, MLflow)</li><li>Experience designing, tuning, and evaluating machine learning models</li><li>Knowledge of data pipelines, basic backend development, and infrastructure awareness</li><li>Comfortable with ambiguity, iteration, and early-stage product work</li><li>Familiarity with model interpretability tools and techniques</li></ul> Bonus points<ul><li>Experience in AML, fraud prevention, or transaction monitoring</li><li>Exposure to systems like FCRM, NICE Actimize, RiskShield, or Pega</li><li>CI/CD practices applied to ML systems</li><li>interest in generative AI and prompt engineering</li></ul> Why join now?This isn’t just another model or dashboard. You’ll help us design the foundations of a new AML product with real-world stakes. You’ll work closely with smart engineers, learn from real customer data, and push the boundaries of what’s possible in fraud detection.If you want to grow your skills, have real impact, and build something from day one…we’d love to hear from you. Apply now or reach out to chat.

Job Description:Principal Associate, Data Scientist - US Card Acquisitions 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 Acquisitions Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions of a new credit card customer. 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 through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: 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. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. 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. 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 one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) 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 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. McLean, VA: $158,600 - $181,000 for Princ Associate, Data Science New York, NY: $173,000 - $197,400 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 Description:Job Family:Data Science Consulting Travel Required:Up to 25% Clearance Required:Ability to Obtain Public Trust What You Will Do: We are seeking an experienced Senior Data Scientist to join our AI and Data practice, supporting transportation and federal civilian agency initiatives. This hands-on leader will provide strategic advice, technical oversight, and direct support for data-driven projects. The role requires expertise in advanced analytics, data governance, and AI/ML, enabling clients to achieve mission outcomes and operational efficiency. Key Responsibilities: Serve as a trusted advisor on data strategy, governance, and analytics modernization Lead engagements from strategy through implementation, ensuring delivery excellence and measurable outcomes Design and oversee AI/ML and analytics solutions using platforms such as Databricks, Snowflake, Azure/AWS/GCP Develop, maintain, and enhance Python-based tools and scripts for data analysis, automation, and reporting Apply CRISP-DM, Agile Kanban, and human-centered design methodologies to deliver impactful solutions Mentor multidisciplinary teams, fostering innovation and continuous learning Collaborate with stakeholders to translate business challenges into actionable data solutions Support business development through proposal writing and strategic pursuits Drive adoption of data culture and literacy through enablement resources, training, and community of practice sessions What You Will Need:US Citizenship is requiredBachelor's degree required Minimum FIVE (5) years of hands-on data science, engineering, and analytics experience Minimum TWO (2) years delivering data-driven transformation programs Expertise in Python for data analysis, automation, and model development, including experience with libraries such as Pandas, NumPy, scikit-learn, and data visualization tools Experience with R, PowerBI, MicroStrategy, and cloud analytics environments Strong understanding of AI/ML technologies, data platforms, and analytics methodologies Experience developing and delivering self-service data products, dashboards, and AI/ML solutions Demonstrated experience in business development lifecycle Proven track record leading large-scale analytics and AI engagements Ability to collaborate across technical and business audiences Excellent communication, facilitation, and relationship-building skills What Would Be Nice To Have:Master's Degree AI/LLM Certifications Project Management Professional (PMP) Experience with federal contracting and procurement processes Familiarity with DAMA-DMBOK, DCAT, and federal data governance frameworks The annual salary range for this position is $130,000.00-$216,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Job Description:Principal Data Scientist, AI Foundations 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 AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One's award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One's digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. Leverage a broad stack of technologies -- Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more -- to reveal the insights hidden within huge volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features. Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80million customers. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate is: 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. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms. Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences. You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF. You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) Preferred Qualifications: Master's Degree in STEM field (Science, Technology, Engineering, or Mathematics), or PhD in STEM field (Science, Technology, Engineering, or Mathematics) Experience working with AWS At least 3 years' experience in Python, Scala, or R 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. McLean, VA: $158,600 - $181,000 for Princ Associate, Data Science New York, NY: $173,000 - $197,400 for Princ Associate, Data Science San Jose, CA: $173,000 - $197,400 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).

About LendableLendable is on a mission to make consumer finance amazing: faster, cheaper, and friendlier. We're building one of the world’s leading fintech companies and are off to a strong start: <ul><li>One of the UK’s newest unicorns with a team of just over 600 people</li><li>Among the fastest-growing tech companies in the UK</li><li>Profitable since 2017</li><li>Backed by top investors including Balderton Capital and Goldman Sachs</li><li>Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on <a>Trustpilot</a>)</li></ul> So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes. Join us if you want to<ol><li>Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1</li><li>Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo</li><li>Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting</li></ol> About the roleWe are excited to be hiring a new Senior Data Scientist for our team! Ideally, this role will suit someone with a proven background in building models ideally in credit, lending, or other areas of financial services. Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits at the heart of this USP, developing the credit risk models to underwrite loan and credit card products.You will have access to the latest machine learning techniques combined with a rich data repository to deliver best in market risk models.This role will primarily focus on our US unsecured loans and credit cards business. Our team’s objectives<ul><li>The data science team develops proprietary machine learning models combining state-of-the-art techniques with a variety of data sources that inform scorecard development and risk management, optimise marketing and pricing, and improve operations efficiency.</li><li>Research new data sources and unstructured data representation.</li><li>Data scientists work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.</li><li>Deliver data services to a wide variety of stakeholders by engineering CLI programs / APIs.</li><li>Design, implement, manage and evaluate experiments of products and services leading to constant innovation and improvement.</li></ul> How you’ll impact those objectives<ul><li>Use your expertise to build and deploy models that contribute to the success of the business.</li><li>Stay up to date with the latest advancements in machine learning and credit risk modelling proactively proposing new approaches and projects that drive innovation.</li><li>Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling.</li><li>Extract, parse, clean and transform data for use in machine learning.</li><li>Clearly communicate results to stakeholders through verbal and written communication.</li><li>Mentor other data scientists and promote best practices throughout the team and business.</li></ul> Key Skills<ul><li>Knowledge of machine learning techniques and their respective pros and cons.</li><li>Ability to communicate sophisticated topics clearly and concisely.</li><li>Proficiency with creating ML models in Python with experiment tracking tools, such as MLFlow.</li><li>Curiosity, creativity, resourcefulness and a collaborative spirit.</li><li>Interest in problems related to the financial services domain - a knowledge of loan or credit card underwriting is advantageous.</li><li>Confident communicator and contributes effectively within a team environment.</li><li>Experience mentoring or leading others.</li><li>Self-driven and willing to lead on projects / new initiatives.</li><li>Familiarity with data used within credit risk decisioning such as Credit Bureau data, especially across multiple geographies is an advantage.</li></ul> The interview processWe’re not corporate, so we try our best to get things moving as quickly as possible. For this role, we’d expect:<ul><li>A quick phone call with the people team</li><li>Interview with hiring manager</li><li>Take home task</li><li>Task debrief</li><li>Case study interview</li><li>In person interview where you'll do your final round and have some lunch with the team</li></ul> Life at Lendable<ul><li>The opportunity to scale up one of the world’s most successful fintech companies.</li><li>Best-in-class compensation, including equity.</li><li>You can work from home every Monday and Friday if you wish - on the other days, those based in the UK come together IRL at our Shoreditch office in London to be together, build and exchange ideas.</li><li>Enjoy a fully stocked kitchen with everything you need to whip up breakfast, lunch, snacks, and drinks in the office every Tuesday-Thursday.</li><li>We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes to private health insurance</li><li>We're an equal-opportunity employer and are looking to make Lendable the most inclusive and open workspace in London</li></ul>Check out our <a>blog</a>!

JOB TITLE: Lead Data Scientist (Gen AI, Python, SQL) JOB LOCATION: St. Petersburgh, FL or Denver, CO Preferred (Hybrid) (other possible locations Southfield, MI/Memphis, TN or NYC WAGE RANGE*: $100-110/hr. JOB NUMBER: 36595992 Required Experience <ul><li>Senior level DS centric role that needs 3+ years of real world DS experience and current.</li><li>Must have strong Python and SQL skills</li><li>Experience required is more on the GEN AI side than it will be on the ML side from a DS perspective</li></ul> JOB DESCRIPTION: The Lead Data Scientist supports development of advanced decision support systems by employing advanced techniques from data analytics (including statistical analysis) and machine learning, particularly including NLP. The successful candidate will join an innovative and energetic team that develops capabilities that improve the performance of our business units and make them more efficient. This is a hands-on role in which the Data Scientist is expected to carry out a project from start to finish. Skills* Excellent communication skills, with the ability to explain technical concepts to a non-technical audience * Strong knowledge of Machine Learning techniques, including NLP but the focus is more on the GEN Ai side than ML side * Knowledge of statistics, including hypothesis testing * Strong Python skills * Proficient in SQL * Comfortable with Unix scripting * Experience building models that actually delivered value to a business * Experience deploying systems to a production environment * Experience working in an Agile environment * Working knowledge of "big data" technologyEducation* Minimum of a Bachelor's degree and six (6) years of relevant experience or combination of education, training and experience. Equal opportunity employer as to all protected groups, including protected veterans and individuals with disabilities * While an hourly range is posted for this position, an eventual hourly rate is determined by a comprehensive salary analysis which considers multiple factors including but not limited to: job-related knowledge, skills and qualifications, education and experience as compared to others in the organization doing substantially similar work, if applicable, and market and business considerations. Benefits offered include medical, dental and vision benefits; dependent care flexible spending account; 401(k) plan; voluntary life/short term disability/whole life/term life/accident and critical illness coverage; employee assistance program; sick leave in accordance with regulation. Benefits may be subject to generally applicable eligibility, waiting period, contribution, and other requirements and conditions. Benefits offered are in accordance with applicable federal, state, and local laws and subject to change at TCM's discretion.PDN-a06bae9b-1957-46ed-9db9-efbaa7262754

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

Myntra Data Scientist Interview Questions + Guide in 2025

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