Sam's Club
Join to apply for the
(USA) Principal, Data Scientist
role at
Sam's Club .
Be among the first 25 applicants.
Base pay range $110,000.00/yr - $220,000.00/yr
As a Principal Data Scientist, you will be the senior individual contributor driving the science and platform foundations for Sam’s Club’s centralized testing and measurement program. Reporting to the Director of Testing & Measurement, you will architect and ship core components of a single experimentation and measurement platform, launch self‑serve capabilities that enable most partners to run rigorous studies independently, and personally lead the most complex ~20% of designs where expert judgment is required. Starting with in‑club measurement, you’ll set the bar for scientific rigor, build reusable libraries and guardrails, and translate ambiguous problems into confident, high‑impact decisions.
What You’ll Do
Establish the scientific standard: Inventory current experimentation practices, KPIs, and data sources; define a shared taxonomy and a Testing & Measurement Playbook (experiment types, MDE/power guidance, preregistration templates, readout standards, guardrails).
Design core platform components: Partner with Engineering to define and begin implementing key services and libraries: variant assignment/bucketing, experiment registry schemas, metrics computation layer, A/A health checks, MDE/power calculators, variance‑reduction utilities (e.g., CUPED), sequential testing controls, and reproducibility tooling.
Launch self‑serve experimentation: Deliver guided workflows that allow ~80% of standard tests to run without DS intervention (preregistration, sizing, guardrails, standardized readouts). Train PM/Ops partners; seed a community of practice.
Lead high‑stakes in‑club designs (pilot → scale): Own the design and analysis for complex in‑club initiatives (e.g., operational changes with spillovers, geo rollouts, merchandising resets), selecting and validating appropriate methods (RCTs, difference‑in‑difference, synthetic controls, stratified matching, geospatial clustering).
Institutionalize rigor & governance (ongoing): Enforce preregistered hypotheses, success/stop criteria, guardrails (member experience, ops impacts), and proper multipletesting and sequential controls; publish reproducible notebooks and code for every readout.
Advance the metrics layer & decision quality: Define and implement a unified metrics catalog/semantic layer (definitions, windows, filters, seasonality/traffic normalization, club clustering).
Mentor and elevate the craft: Lead code reviews, design reviews, brownbag sessions; build exemplars (notebooks, libraries, docs) that raise the bar for the team and community.
Champion privacy, compliance, and auditability: Embed identity, privacy, and legal considerations into assignment, data joins, and reporting; ensure full audit trails.
What You’ll Bring
Causal Inference & Experimentation Depth: Mastery of RCTs and quasi‑experimental methods (difference‑in‑difference, synthetic controls, matched/stratified designs, interrupted time series), power/MDE analysis, sequential testing control, heterogeneity analysis, and variance reduction (e.g., CUPED).
Platform‑level Engineering Mindset: Experience architecting or scaling experimentation/measurement platforms (assignment services, experiment registry, metrics pipelines, readout services, observability), with strong collaboration alongside engineering.
Hands‑on Technical Skills: Deep proficiency in Python for machine learning and statistical modeling, with strong experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit\-learn) and data manipulation libraries (Pandas, NumPy); proficient in SQL for feature engineering and large‑scale data extraction; committed to production‑grade practices including code quality, automated testing, reproducibility, and model lifecycle management (MLOps).
In‑Club/Physical Retail Measurement Advantage: Practical approaches to traffic normalization, seasonality/weather shocks, operational spillovers, and club clustering/geospatial matching.
Business Acumen & Communication: Ability to distill noisy signals into concise, decision‑oriented narratives and influence senior stakeholders with clarity and credibility.
Leadership Without Authority: Track record of mentoring, setting scientific standards, and driving adoption of consistent practices across multiple teams.
Education: BS/MS/PhD in a quantitative field (Statistics, Economics, Computer Science, etc.) or equivalent experience.
Benefits
Health benefits: medical, vision and dental coverage.
Financial benefits: 401(k), stock purchase and company‑paid life insurance.
Paid time off: PTO, parental leave, family care leave, bereavement, jury duty, voting; PTO/PPTO available for vacation, sick leave, holidays or other purposes.
Other benefits: short‑term and long‑term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.
Live Better U: Company‑paid education benefit program covering high school completion to bachelor’s degrees, including English language learning and short‑form certificates; tuition, books, and fees are paid by Walmart.
For information about PTO, see https://one.walmart.com/notices.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
The annual salary range for this position is $110,000.00-$220,000.00.
Additional Compensation Includes Annual Or Quarterly Performance Bonuses.
Minimum Qualifications
Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
Option 3: 7 years' experience in an analytics or related field.
Preferred Qualifications
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, publications or active peer reviewer in related journals or conference.
Successful completion of one or more assessments in Python, Spark, Scala, or R; using open source frameworks (for example, scikit\-learn, TensorFlow, Torch).
Background in creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly; knowledge of accessibility best practices and commitment to Walmart’s accessibility standards and guidelines.
Primary Location 2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
Industries: Retail
Other Information Walmart and its subsidiaries are committed to maintaining a drug‑free workplace and have a no‑tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.
#J-18808-Ljbffr
(USA) Principal, Data Scientist
role at
Sam's Club .
Be among the first 25 applicants.
Base pay range $110,000.00/yr - $220,000.00/yr
As a Principal Data Scientist, you will be the senior individual contributor driving the science and platform foundations for Sam’s Club’s centralized testing and measurement program. Reporting to the Director of Testing & Measurement, you will architect and ship core components of a single experimentation and measurement platform, launch self‑serve capabilities that enable most partners to run rigorous studies independently, and personally lead the most complex ~20% of designs where expert judgment is required. Starting with in‑club measurement, you’ll set the bar for scientific rigor, build reusable libraries and guardrails, and translate ambiguous problems into confident, high‑impact decisions.
What You’ll Do
Establish the scientific standard: Inventory current experimentation practices, KPIs, and data sources; define a shared taxonomy and a Testing & Measurement Playbook (experiment types, MDE/power guidance, preregistration templates, readout standards, guardrails).
Design core platform components: Partner with Engineering to define and begin implementing key services and libraries: variant assignment/bucketing, experiment registry schemas, metrics computation layer, A/A health checks, MDE/power calculators, variance‑reduction utilities (e.g., CUPED), sequential testing controls, and reproducibility tooling.
Launch self‑serve experimentation: Deliver guided workflows that allow ~80% of standard tests to run without DS intervention (preregistration, sizing, guardrails, standardized readouts). Train PM/Ops partners; seed a community of practice.
Lead high‑stakes in‑club designs (pilot → scale): Own the design and analysis for complex in‑club initiatives (e.g., operational changes with spillovers, geo rollouts, merchandising resets), selecting and validating appropriate methods (RCTs, difference‑in‑difference, synthetic controls, stratified matching, geospatial clustering).
Institutionalize rigor & governance (ongoing): Enforce preregistered hypotheses, success/stop criteria, guardrails (member experience, ops impacts), and proper multipletesting and sequential controls; publish reproducible notebooks and code for every readout.
Advance the metrics layer & decision quality: Define and implement a unified metrics catalog/semantic layer (definitions, windows, filters, seasonality/traffic normalization, club clustering).
Mentor and elevate the craft: Lead code reviews, design reviews, brownbag sessions; build exemplars (notebooks, libraries, docs) that raise the bar for the team and community.
Champion privacy, compliance, and auditability: Embed identity, privacy, and legal considerations into assignment, data joins, and reporting; ensure full audit trails.
What You’ll Bring
Causal Inference & Experimentation Depth: Mastery of RCTs and quasi‑experimental methods (difference‑in‑difference, synthetic controls, matched/stratified designs, interrupted time series), power/MDE analysis, sequential testing control, heterogeneity analysis, and variance reduction (e.g., CUPED).
Platform‑level Engineering Mindset: Experience architecting or scaling experimentation/measurement platforms (assignment services, experiment registry, metrics pipelines, readout services, observability), with strong collaboration alongside engineering.
Hands‑on Technical Skills: Deep proficiency in Python for machine learning and statistical modeling, with strong experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit\-learn) and data manipulation libraries (Pandas, NumPy); proficient in SQL for feature engineering and large‑scale data extraction; committed to production‑grade practices including code quality, automated testing, reproducibility, and model lifecycle management (MLOps).
In‑Club/Physical Retail Measurement Advantage: Practical approaches to traffic normalization, seasonality/weather shocks, operational spillovers, and club clustering/geospatial matching.
Business Acumen & Communication: Ability to distill noisy signals into concise, decision‑oriented narratives and influence senior stakeholders with clarity and credibility.
Leadership Without Authority: Track record of mentoring, setting scientific standards, and driving adoption of consistent practices across multiple teams.
Education: BS/MS/PhD in a quantitative field (Statistics, Economics, Computer Science, etc.) or equivalent experience.
Benefits
Health benefits: medical, vision and dental coverage.
Financial benefits: 401(k), stock purchase and company‑paid life insurance.
Paid time off: PTO, parental leave, family care leave, bereavement, jury duty, voting; PTO/PPTO available for vacation, sick leave, holidays or other purposes.
Other benefits: short‑term and long‑term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.
Live Better U: Company‑paid education benefit program covering high school completion to bachelor’s degrees, including English language learning and short‑form certificates; tuition, books, and fees are paid by Walmart.
For information about PTO, see https://one.walmart.com/notices.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
The annual salary range for this position is $110,000.00-$220,000.00.
Additional Compensation Includes Annual Or Quarterly Performance Bonuses.
Minimum Qualifications
Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
Option 3: 7 years' experience in an analytics or related field.
Preferred Qualifications
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, publications or active peer reviewer in related journals or conference.
Successful completion of one or more assessments in Python, Spark, Scala, or R; using open source frameworks (for example, scikit\-learn, TensorFlow, Torch).
Background in creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly; knowledge of accessibility best practices and commitment to Walmart’s accessibility standards and guidelines.
Primary Location 2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
Industries: Retail
Other Information Walmart and its subsidiaries are committed to maintaining a drug‑free workplace and have a no‑tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.
#J-18808-Ljbffr