Senior Data Scientist – Customer Analytics, Measurement
Staples Promotional Products
full-time
Posted on:
Location Type: Hybrid
Location: Framingham • Massachusetts • 🇺🇸 United States
Visit company websiteJob Level
Senior
Tech Stack
PythonSQL
About the role
- Design and maintain customer segmentation frameworks using large-scale transactional, behavioral, and engagement data.
- Develop segmentation strategies based on lifecycle stage, purchase frequency, basket composition, category affinity, promotion responsiveness, and channel preference.
- Build and deploy personalization and targeting models (e.g., propensity, uplift, ranking) to improve engagement, conversion, and retention across marketing and customer touchpoints.
- Translate analytical and model outputs into actionable decisioning logic.
- Design, analyze, and interpret experiments and quasi-experiments across marketing, merchandising, and customer engagement use cases.
- Apply causal inference techniques such as A/B testing, difference-in-differences, matching, uplift modeling, and other incrementality approaches.
- Support experiments conducted at multiple levels, including customer-, geo-, and store-level designs, while accounting for seasonality, spillover effects, and operational constraints.
- Partner with stakeholders to ensure tests are well-powered, statistically sound, and aligned with business objectives.
- Build and evolve omnichannel measurement frameworks, including multi-touch attribution and incrementality models, to assess the impact of customer and marketing touchpoints.
- Measure the effectiveness of digital and offline channels, such as paid media, email, loyalty programs, promotions, and in-store activity.
- Clearly communicate model assumptions, limitations, and tradeoffs to technical and non-technical audiences to support decision-making.
- Collaborate with Analytics and Data Engineering teams to define clean, reliable, and scalable data models at the SKU, transaction, store, and customer level.
- Productionize analytical models and data products using best practices for code quality, versioning, validation, monitoring, and retraining.
- Write maintainable, well-documented code and contribute to shared data science tooling and standards.
- Act as a senior individual contributor and technical leader, setting a high bar for analytical rigor and statistical judgment.
- Review and provide feedback on analyses and models developed by other data scientists.
- Proactively identify opportunities where data science can improve customer experience, marketing efficiency, and commercial outcomes.
- Influence strategy with data-driven insights.
Requirements
- 7+ years experience in Data Science, Analytics Engineering, ML Engineering, or related roles.
- Strong foundation in statistics, probability, experimental design, and causal inference.
- Demonstrated experience with customer analytics, including segmentation, personalization, or marketing measurement.
- Hands-on experience designing and analyzing experiments and observational studies in real-world business settings.
- Proficiency in Python and SQL.
- Experience deploying models into production.
- Ability to communicate complex technical concepts clearly to non-technical stakeholders.
Benefits
- Generous amount of paid time off and bonus plan.
- 401(k) plan with a company match, medical, dental, vision, life and disability insurance, and many more benefits.
- Associate store discount and more perks (discounts on mobile plans, movie tickets, etc.).
- On-site, discounted childcare, fitness center and dry cleaners in Framingham, MA corporate office.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
customer segmentationsegmentation strategiespersonalization modelstargeting modelsA/B testingcausal inferencePythonSQLdata modelinganalytical models
Soft skills
communicationcollaborationanalytical rigorstatistical judgmentinfluence strategyfeedbackproactive identificationdecision-makingstakeholder partnershiptechnical leadership