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

Statistics

What is the difference between the Z and t tests?

Z and t-Tests

Size of Joins

Data Structures & Algorithms

String Shift

Machine Learning

choosing k value during k-means clustering

Choosing k

In an A/B test, how can you check if assignment to the various buckets was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

Random Bucketing

A/B Testing

Let’s say that Facebook would like to change the user interface of the composer feature (the posting box) to be more like Instagram. Instead of a box, Facebook would add a “+” button at the bottom of the page.

How would you test if this is a good idea?

What could be a potential risk when Facebook segments the results of the user interface change by market or demographic groups?

What could be a potential risk when Facebook segments the results of the user interface change by market or demographic groups?

Changing Composer I

What is the primary metric that Facebook should monitor if it decides to make the user interface of its posting feature more like Instagram's?

What is the primary metric that Facebook should monitor if it decides to make the user interface of its posting feature more like Instagram's?

Changing Composer II

Changing Composer

Let’s say at Netflix we offer a subscription where customers can enroll for a 30-day free trial. After 30 days, customers will be automatically charged based on the package selected.

Let’s say we want to measure the success of acquiring new users through the free trial.

How can we measure acquisition success and what metrics can we use to measure the success of the free trial?

Let’s say we want to measure the effectiveness of Netflix’s 30-day free trial plan.

What is NOT a metric we would use?

Let's say we want to measure the effectiveness of Netflix's 30-day free trial plan.

What is NOT a metric we would use?

Netflix Retention

How do we measure the success of acquiring new users through a free trial

Product Sense & Metrics

Swiggy Data Scientist Interview Questions

Job Family :
Data Science Consulting
Travel Required :
Up to 10%
Clearance Required :
Ability to Obtain Public Trust

About our AI and Data Capability Team
Our consultants on the AI and Data Analytics Capability team help clients maximize the value of their data and automate business processes. This high performing team works with clients to implement the full spectrum of data analytics and data science services, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as intelligent automation. Our services enable our clients to define their information strategy, enable mission critical insights and data-driven decision making, reduce cost and complexity, increase trust, and improve operational effectiveness.

What You Will Do :
Data Collection & Management: Identify, gather, and manage data from primary and secondary sources, ensuring its accuracy and integrity.
Data Cleaning & Preprocessing: Clean raw data by identifying and addressing inconsistencies, missing values, and errors to prepare it for analysis.
Data Analysis & Interpretation: Apply statistical techniques and analytical methods to explore datasets, discover trends, find patterns, and derive insights.
Data Visualization & Reporting: Develop reports, dashboards, and visualizations using tools like Tableau or Power BI to present complex findings clearly to stakeholders.
Collaboration & Communication: Work with cross-functional teams, understand business requirements, and effectively communicate insights to support data-driven decision-making.
Problem Solving: Address specific business challenges by using data to identify underperforming processes, pinpoint areas for growth, and determine optimal strategies.

What You Will Need :
US Citizenship is required
Bachelor's degree is required
Minimum THREE (3) Years Experience using Power BI, Tableau and other visualization tools to develop intuitive and user friendly dashboards and visualizations.
Skilled in SQL, R, and other languages to assist in database querying and statistical programming.
Strong foundational knowledge and experience in statistics, probability, and experimental design.
Familiarity with cloud platforms (e.g., Amazon Web Services, Azure, or Google Cloud) and containerization (e.g., Docker).
Experience applying data governance concepts and techniques to assure greater data quality and reliability.
he curiosity and creativity to uncover hidden patterns and opportunities.
Strong communication skills to bridge technical and business worlds.

What Would Be Nice To Have :
Hands-on experience with Python, SQL, and modern ML frameworks.
Experience in data and AI system development, with a proven ability to design scalable architectures and implement reliable models.
Expertise in Python or Java for data processing.
Demonstrated work experience within the public sector.
Ability to support business development including RFP/RFQ/RFI responses involving data science / analytics.

#LI-DNI

The annual salary range for this position is $113,000.00-$188,000.00. 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 EmployerProtected 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 Guidehouses 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 applicants 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 DescriptionWe are seeking a Data Scientist to work on product, customer, and business data for a scalable B2B SaaS platform. The role focuses on transforming large volumes of structured and semi-structured data into actionable insights, predictive models, and experimentation frameworks that directly influence product decisions, customer retention, and revenue growth.This position is best suited for candidates with prior experience in B2B SaaS or product-led environments, where data is embedded into daily decision-making.Key Responsibilities<ul><li>Analyze product usage, customer behavior, and transactional data to identify trends, risks, and growth opportunities</li><li>Build and deploy statistical and machine learning models for:</li><li>Customer churn prediction</li><li>Retention and engagement analysis</li><li>Usage forecasting and demand modeling</li><li>Design, execute, and evaluate A/B tests and experiments for product and growth initiatives</li><li>Collaborate with Product Managers, Engineering, Marketing, and Business teams to define data-driven strategies</li><li>Develop dashboards and reports tracking SaaS metrics such as activation, retention, churn, LTV, and conversion funnels</li><li>Ensure data accuracy, quality checks, and monitoring for analytics pipelines</li><li>Communicate insights clearly to technical and non-technical stakeholders</li></ul>Qualifications<ul><li>3+ years of experience as a Data Scientist in a B2B SaaS or product-based company</li><li>Strong proficiency in Python (Pandas, NumPy, Scikit-learn)</li><li>Advanced SQL skills with experience querying large datasets</li><li>Solid foundation in statistics, probability, and machine learning</li><li>Experience working with SaaS business metrics (churn, retention, cohorts, funnel analysis)</li><li>Experience with cloud platforms (AWS, GCP, or Azure)</li><li>Ability to translate business problems into data science solutions</li></ul>

divh2Senior Data Scientist/h2pIn the role of Data Scientist, you will report to the Director of Machine Learning and Data Science. We are considering applicants for the location(s) of Los Angeles, CA or San Francisco. We are seeking a skilled Data Scientist to join our innovative team, working closely with Senior Data Scientists and Machine Learning Engineers to maintain, enhance, and innovate our suite of machine learning and AI-driven models and services. This role will focus on critical areas such as churn and winback predictions, predictive lifetime value (LTV), financial forecasting, title- and catalog-level KPI forecasting (e.g., acquisition, viewership), high-value action analysis in subscriber lifecycle management, user behavior modeling with applications in fraud-detection and recommendation systems. The ideal candidate will bring a strong foundation in statistical and machine learning fundamentals, coupled with expertise in modern data science tech stacks, to drive impactful solutions for both consumer-facing and stakeholder-oriented initiatives./ppCore Areas of Responsibility:/pulliDevelop and implement new models or enhancements to drive innovation in predictive analytics and personalized user experiences./liliAnalyze large-scale datasets to uncover insights, identify trends, and inform model development and optimization./liliApply statistical and machine learning techniques to solve complex business problems and improve model performance./liliWork with modern data processing tools, modeling frameworks, MLOps pipelines, and cloud infrastructure to ensure efficient and scalable workflows./liliPartner with cross-functional teams, including Machine Learning Engineers, AI Engineers, and Platform/Software Engineers, to integrate models into production environments./liliDocument methodologies, experiments, and findings to support team collaboration and knowledge sharing./liliStay current with advancements in data science, machine learning, and related technologies to bring cutting-edge approaches to our solutions./li/ulpAbout You:/pulliMasters degree in Data Science, Statistics, Computer Science, Mathematics, or a related field./liliStrong understanding of statistical and machine learning fundamentals and their practical applications./liliProven experience in developing and optimizing machine learning models for predictive analytics, forecasting, or recommendation systems./liliProficiency in Python and familiarity with data science libraries such as pandas, NumPy, scikit-learn, statsmodels, TensorFlow, or PyTorch./liliExperience with modern data processing tools (e.g., Apache Spark, SQL) and cloud infrastructure and services (e.g., AWS, Google Cloud, Databricks)./liliFamiliarity with MLOps practices and tools (e.g., Version Control, Pipelines, Containerization, and Orchestration) for model testing, deployment and monitoring./liliStrong analytical and problem-solving skills with a focus on delivering actionable insights./liliExcellent communication and collaboration skills to work effectively with interdisciplinary teams./li/ulpPluses:/pulliExperience with churn prediction, customer lifetime value modeling, financial forecasting with time series or deep learning models, or recommendation systems in a consumer-facing industry./liliKnowledge of advanced statistical methods, such as Bayesian modeling or causal inference./liliUnderstanding of subscriber lifecycle management and high-value action analysis./liliComfortable with imperfect and evolving data, working with raw data such as events, and seeking solutions to improve data qualities./li/ulpAbout the Team:/ppYou will join an interdisciplinary team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and ML/AI to create transformative solutions. Our team delivers both consumer-facing product features that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our teams culture as we work together to push the boundaries of whats possible in streaming and data-driven decision-making./ppWhy you will love working at Crunchyroll:/pulliReceive a great compensation package including salary plus performance bonus earning potential, paid annually./liliFlexible time off policies allowing you to take the time you need to be your whole self./liliGenerous medical, dental, vision, STD, LTD, and life insurance/liliHealth Saving Account HSA program/liliHealth care and dependent care FSA/lili401(k) plan, with employer match/liliEmployer paid commuter benefit/liliSupport program for new parents/liliPet insurance and some of our offices are pet friendly!/li/ulpThe Pay Range for this position is listed. Actual pay will vary based on factors including, but not limited to location, experience, and performance. The range listed is just one component of Crunchyrolls Total Rewards offerings for employees. Other rewards may include performance bonuses, employer matched retirement savings, time-off programs, and progressive health benefits and perks./ppPay Transparency - Los Angeles, CA/pp$167,000 - $209,000 USD/ppAbout Our Values:/pulliCourage: We believe that when we overcome fear, we enable our best selves./liliCuriosity: We are curious, which is the gateway to empathy, inclusion, and understanding./liliKaizen: We have a growth mindset committed to constant forward progress./liliService: We serve our community with humility, enabling joy and belonging for others./li/ulpOur Commitment to Diversity and Inclusion:/ppOur mission of helping people belong reflects our commitment to diversity inclusion. Its just the way we do business./ppWe are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status./ppCrunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japans Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation./p/div

Dear Tech Professional Greetings from Tata Consultancy Services TCS has always been in the spotlight for being adept in “the next big technologies”. What we can offer you is a space to explore varied technologies and quench your techie soul. What we are looking for: Data ScientistLocation: Chennai, Hyderabad, Kolkata, MumbaiInterview Mode: Virtual mode (Microsoft Teams) Exp: 5-10 Years <ul><li>5+ years of professional experience in data science, machine learning</li><li>Strong proficiency in Python is mandatory, with experience in data science libraries like NumPy, Pandas, and Scikit-learn. Knowledge of SQL is also essential for data extraction and manipulation</li><li>Expertise in deep learning frameworks such as PyTorch and TensorFlow. Familiarity with Hugging Face transformers, NLTK, or SpaCy is also common.</li><li>Hands-on experience with major cloud computing services (<a>AWS</a>, Azure, GCP) for model deployment and leveraging services like Azure OpenAI, Google Vertex AI, or AWS Bedrock.</li><li>Strong analytical, problem-solving, and statistical skills. </li></ul> RegardsPrashaanthini

<h5>Data Scientist NLP/ML (Call Center Transcripts) </h5>Location: Remote (CST Preferred) Duration: 12 Months Top Skills: NLP SQL Python Tech Stack / Focus Areas: Natural Language Processing (NLP) Machine Learning (focused on NLP) Python & SQL Automation techniques Transformers Text and transcript data (member phone...

Staff Data Scientist Sales Analytics Location: San Francisco (Hybrid) Salary: $200250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. Were looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel. About the Role As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth. Key Responsibilities <ul> <li>Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections. </li><li>Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates. </li><li>Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives. </li><li>Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects. </li><li>Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions. </li><li>Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting. </li><li>Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations. </li></ul> About You <ul> <li>Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments. </li><li>Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning. </li><li>Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions. </li><li>Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy. </li><li>Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams. </li><li>Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes. </li></ul>

<h5>Senior Data Scientist </h5>The Senior Data Scientist is a hybrid role at LegalShield that blends data science, applied machine learning, and platform engineering to build and operationalize AI solutions that drive business impact. The position focuses equally on developing advanced predictive and generative models and on designing the scalable infrastructure required to deploy them securely and efficiently. As a key technical leader, you'll work on end-to-end ML initiativesfrom feature engineering and model experimentation to deploying production-grade APIs and orchestration systems. This includes fine-tuning large language models for LegalShield-specific use cases, such as analyzing call transcripts, understanding customer sentiment, and generating personalized content. You'll also ensure models meet high standards of accuracy, fairness, and compliance while translating insights into actionable business strategies. Beyond modeling, this position plays a vital role in platform enablement. You'll build the systems that make AI usable across LegalShield, including containerized deployment pipelines, monitoring frameworks, and governance tools that meet SOC2, HIPAA, and GDPR standards. By developing both internal productivity tools and external member-facing AI applications, you'll help shape LegalShield's broader AI strategyworking closely with the Director of Data Science, the CTO, and cross-functional business leaders to embed intelligent solutions across the organization. In short, this role combines innovation with scalabilitybridging the gap between research and production to make AI a core enabler of LegalShield's growth and customer experience. <h5>Responsibilities </h5>Performance Outcomes <ul> <li>Develop predictive and generative ML models to support acquisition, retention, personalization, and member engagement. </li><li>Fine-tune and adapt Large Language Models (LLMs) for LegalShield-specific use cases, including call transcript analysis, voice-of-customer workflows, and content generation. </li><li>Conduct experimentation, model evaluation, and rigorous validation to ensure accuracy, fairness, and business alignment. </li><li>Partner with business teams to design experiments, analyze results, and translate insights into actionable strategies. </li></ul> Platform & Productionization <ul> <li>Build and maintain infrastructure for deploying and scaling ML/GenAI models. </li><li>Develop APIs, MCP servers and microservices to serve models across internal and external applications. </li><li>Translate prototypes into production-grade systems for business and member-facing teams. </li><li>Implement CI/CD pipelines, containerization, and orchestration (Docker, Kubernetes). </li><li>Deploy and manage ML workflow orchestration, feature stores, and model registries. </li><li>Monitor and optimize performance, drift, latency, and cloud costs. </li><li>Ensure compliance with SOC2, HIPAA, GDPR, and other data privacy/security standards. </li></ul> AI Tooling & Applications <ul> <li>Develop internal AI tools that improve productivity and deliver measurable cost savings. </li><li>Develop external, member-facing AI-powered applications that create new value and enhance customer experience. </li><li>Build reusable platforms and tools that accelerate AI/ML adoption across LegalShield. </li></ul> <h5>Education, Knowledge, and Experience </h5><ul> <li>Advanced degree in Data Science, Statistics, Computer Science, or a related field (or equivalent practical experience). </li><li>7+ years' experience in software engineering, Machine Learning, or Applied Data Science (Python preferred; APIs, microservices, distributed systems). </li><li>Proven ability to take AI/ML solutions from prototype to production and scale adoption across teams. </li><li>Hands-on experience with Large Language Models (LLMs) and retrieval-augmented generation (RAG) pipelines, LLM Fine-tuning and training. </li><li>Familiarity with ML infrastructure: feature stores, model registries, or workflow orchestration tools. </li><li>Experience with CI/CD, Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure). </li><li>Understanding of compliance and data privacy standards, and ability to apply them in AI systems. </li><li>Proven track record of deploying and operating ML/AI systems in production. </li></ul> Preferred: <ul> <li>Deep knowledge of ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain). </li><li>Experience building shared AI/ML platforms or internal developer tools. </li><li>Familiarity with observability and Cataloging tools (Snowflake, Secoda, Airflow). </li><li>Prior experience working cross-functionally with data science, infrastructure, and product teams. </li></ul> Performance Outcomes: <ul> <li>Successful development and maintenance of data systems and solutions, as described in the responsibilities above. </li><li>Successful engagement and collaboration with others: Work closely and effectively with teammates, which may include data engineers, software engineers, program/product managers, software test engineers, and others. </li><li>Contribute to the implementation of dynamic requirements/initiatives with teammates, cross-team collaborators, and with business partners as appropriate. </li></ul> Exempt Physical Requirements/Work Environment The work environment characteristics and physical demands described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. <ul> <li>Prolonged periods of sitting or standing at a desk </li><li>Extensive periods of working on a computer </li></ul> Remote Job Posting

<h5>Data Scientist </h5>Founded in 2007, SimIS Inc. is an innovative information technology solution Veteran Owned Small Business (VOSB) that models future environments, requirements, and capabilities, and then secures the enterprise from internal and external threats compliant with Federal, State, and industry standard governance to ensure client mission success. Our performance standard is "excellence," with an outcomes-based, quality focus in our services and products, guided by our core values of honesty (in word and deed), relationships (confidence and trust with clients and partners), teamwork (shared goals, mission, and purpose), loyalty (allegiance to our client and team), and importance of others (work and win as a team). SimIS is currently recruiting for the listed position and is contingent upon award. The position is anticipated to be "on site." <h5>Job Description: </h5>NATO HQ Supreme Allied Command Transformation (NATO SACT) is seeking contract support for the capture, development, architecture, data science and quality assurance of capability requirements and operational analysis necessary to adapt to future threats and explore long-term military strategy to shape how NATO's forces will operate in the future. To support our NATO customer, SimIS Inc seeks a Data Scientist to apply business and data manipulation principles and methods to technical problems to arrive at solutions that enable the development and integration of emerging technologies to support NATO force design and strategic decision making. <h5>Experience Required: </h5>BS degree in Data Science, Computer Science, or Statistics. 5 years of experience in qualitative and quantitative analysis, including mathematical, statistical and general research. 3 years of experience in production and visualization of quantitative assessments. Expertise in Programming Languages: Python, R, SQL, Spark, TensorFlow/PyTorch. Expertise in Data Visualization tools (Tableau, Power BI, D3.js). Coding knowledge/experience: Java, JavaScript, C, C++, etc. <h5>Responsibilities: </h5>Support of Strategic Foresight and Net Assessment processes with qualitative and quantitative assessments. Interpret data, analyze results using statistical techniques, and visualize assessments and findings. Develop and implement data analyses, data collection systems and other strategies that optimize statistical efficiency and quality. Acquire data from primary or secondary data sources and maintain databases. Support comparative analysis through cross-directorate coordination at NATO ACT. Work across the NATO directorates and joint centers and externally with other stakeholders to define, collate, prioritize and justify military requirements with the NATO capability-based Requirement Area Framework. <h5>Benefits: </h5>Medical, Dental, and Vision Short-Term Disability (at no cost to you) & Long-Term Disability Life Insurance 401(k) Savings Plan Flex Spending Accounts Tuition Assistance Program Professional Development Paid Time Off (PTO) 11 Federal Holidays each year SimIS, Inc. is an EOE / M / F / Disability / VET / Drug Free Employer

Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Mentors and develops junior data scientists and analysts. Role Summary This role leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making, while mentoring junior data scientists and analysts, and applying advanced data science and big data mining techniques to uncover trends, inform strategic initiatives, and drive innovation across diverse business functions. Responsibilities <ul> <li>Develops complex queries and performs extensive programming to access, transform, and prepare data for statistical modeling. </li><li>Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Mentors and develops junior data scientists and analysts. </li><li>Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps. </li><li>Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. </li><li>Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community. </li><li>Prepares and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business leaders. </li><li>Participates in special projects and performs other duties as assigned. </li><li>Designs scalable data mining models and reporting protocols to identify trends and patterns in massive datasets. </li><li>Applies modern and emerging data science techniques to solve business problems across functions such as marketing, economics, and operations. </li><li>Contributes to the advancement of analytics through exploratory research and application of cutting-edge statistical theory. </li></ul> Qualifications and Skills <ul> <li>Minimum 8 years of experience in data science, predictive analytics, or advanced statistical modeling roles </li><li>Bachelors degree (B.E./B.Tech) in Analytics, Applied Mathematics, Economics, Statistics, or Computer Science, or a Masters degree/Diploma in a related quantitative field </li><li>Expertise in programming with Python, R, or SQL; hands-on experience with machine learning libraries (e.g., Scikit-learn, TensorFlow); strong understanding of data pipelines, data wrangling, and statistical techniques; experience in big data environments (Spark/Hadoop); familiarity with visualization tools like Tableau or Power BI </li></ul> Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don't just have a missionwe're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

<h5>Senior Staff Data Scientist </h5>Intuit's Global Business Solutions Group (GBSG) is dedicated to creating tools and services that dramatically increases the ability of small-medium businesses (SMBs) to manage cash flow. At the center of this mission, the QuickBooks Money team is developing innovative tools to help customers get paid faster and with confidence. Our expanding suite of offerings and new go-to-market strategies aim to further enhance SMBs' ability to accept payments seamlessly. The Money Data Science team on the GBSG Data & Analytics organization's mission is to deliver delightful customer experiences and drive business impact by developing insights, models, and strategic thought partnership that helps small and mid-market business customers on managing their money. We partner with Product Management, Commercial, Finance, Business Operations, Design and Engineering teams to foster data-driven decisions through strategic thinking, data analysis, experimentation, and predictive analytics. As the founding Senior Staff Data Scientist working on an accelerating growth for a strategic priority within the company, you will dive deep into our data to uncover actionable insights and make recommendations that will fuel growth of this new product. The ideal candidate will have a strong background in quantitative analysis using large data sets, demonstrated growth hacking experience on mature and high growth products, and in driving influence and alignment with data. Responsibilities As a Senior Staff Data Scientist on the Product Data Science team, you will dive deep into our data to uncover actionable insights and shape strategic decisions. Your contributions will directly impact our product development and GTM strategies of a brand new product and strategic bet. This role requires a strong background in quantitative analysis, data-driven decision-making, and expertise in working with large data sets. <ul> <li>Conceptualize business problems or opportunities, formulate hypotheses and goals, define key metrics and make actionable recommendations </li><li>Drive strategic insights that shape the future of Money-movement ecosystem products within Intuit, impacting millions of small businesses </li><li>Develop predictive models, conduct experimentation beyond A/B testing, and generate actionable customer insights that inform product innovation </li><li>Build and apply durable customer segmentation patterns to renew product targeting, positioning, and customer experience </li><li>Partner closely with Product Management, Marketing, Engineering, Design, and Analytics leaders to deliver insights that drive product strategy and growth </li><li>Translate complex data insights into actionable recommendations for technical and non-technical stakeholders, and business leaders </li></ul> Qualifications The ideal candidate is a curious, proactive data scientist with experience in building scalable solutions, a strong understanding of customer behavior, and a passion for fintech. <ul> <li>BS or MS degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics or related field. Equivalent experience will be considered. </li><li>10+ years of experience in data science or product analytics, preferably in fintech, with a strong foundation in predictive modeling, customer segmentation, and experimentation </li><li>Ability to formulate data-backed strategies that will drive step-function growth for the business as well as increase customer benefit </li><li>Ability to generate hypotheses grounded in customer behavior, industry trends, and external market factors. Experience in the fintech or SMB space is highly preferred. </li><li>Experience in designing and interpreting complex experiments beyond traditional A/B testing methods </li><li>Demonstrated experience in building reusable and scalable analytics solutions, with a focus on efficiency and avoiding duplication of work </li><li>Outstanding communication skills with the ability to influence decision makers and build consensus with teams </li><li>Quick learner, adaptable, with the ability to work independently or as part of a team in a fast-paced environment </li><li>Experience using statistics and machine learning techniques to solve complex business problems within go-to-market and marketing areas, e.g., propensity for feature adoption, customer health scoring to identify customers at risk to cancel, next best action models etc. </li><li>Technical Skills: </li><ul> <li>Advanced SQL skills and proficiency in visualization tools such as Qlik, Tableau, Plotly Dash </li><li>Strong analytical and modeling skills using Python (for its rich suite of statistical and modeling libraries like numpy, pandas, scikit-learn, etc.) </li><li>Familiarity with Linux/OS X command line, version control software (git), and general software development </li></ul> </ul>Preferred Additional Qualifications <ul> <li>Experience solving growth-related problems at financial technology companies serving consumer or SMBs </li><li>Familiarity with Generative AI and other evolving technologies to accelerate insights from multi-modal data </li></ul> Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Bay Area California: $204,500- 276,500 Southern California: $197,500- 267,500

Question	Topic	Difficulty	Ask Chance
Random Bucketing	A/B Testing	Medium	Very High
Changing Composer	A/B Testing	Easy	Very High
Netflix Retention	Product Sense & Metrics	Hard	Very High

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