Sam’s Club
Base pay range
$110,000.00/yr - $220,000.00/yr Position Summary
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 inclub 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 such as 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 and seed a community of practice. Lead high-stakes inclub designs: own the design and analysis for complex inclub initiatives (operational changes with spillovers, geo rollouts, merchandising resets), selecting and validating appropriate methods (RCTs, diff-in-diff, synthetic controls, stratified matching, geospatial clustering). Institutionalize rigor & governance (ongoing): enforce preregistered hypotheses, success/stop criteria, guardrails (member experience, ops impacts), and proper multiple-testing 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 quasiexperimental methods (diff-in-diff, 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 (TensorFlow, PyTorch, Scikit-learn) and data manipulation libraries (Pandas, NumPy). Skilled in SQL for feature engineering and large-scale data extraction. Commitment to production-grade practices including code quality, automated testing, reproducibility, and model lifecycle management (MLOps). InClub/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 & Location
Location: Bentonville, AR. Sam’s Club offers competitive pay and benefits, including health, retirement, and time-off programs. See official eligibility and plans for details. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
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$110,000.00/yr - $220,000.00/yr Position Summary
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 inclub 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 such as 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 and seed a community of practice. Lead high-stakes inclub designs: own the design and analysis for complex inclub initiatives (operational changes with spillovers, geo rollouts, merchandising resets), selecting and validating appropriate methods (RCTs, diff-in-diff, synthetic controls, stratified matching, geospatial clustering). Institutionalize rigor & governance (ongoing): enforce preregistered hypotheses, success/stop criteria, guardrails (member experience, ops impacts), and proper multiple-testing 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 quasiexperimental methods (diff-in-diff, 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 (TensorFlow, PyTorch, Scikit-learn) and data manipulation libraries (Pandas, NumPy). Skilled in SQL for feature engineering and large-scale data extraction. Commitment to production-grade practices including code quality, automated testing, reproducibility, and model lifecycle management (MLOps). InClub/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 & Location
Location: Bentonville, AR. Sam’s Club offers competitive pay and benefits, including health, retirement, and time-off programs. See official eligibility and plans for details. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Retail We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr