Senior Data Scientist

A national industrial distribution organization is seeking a Senior Data Scientist (Operations & Supply Chain) to lead and scale a best-in-class experimentation and test-and-learn strategy across its parts distribution warehouse network. This highly visible role will focus on designing, executing, and measuring complex operational pilots that inform pricing, inventory, and supply chain decisions at scale.
In this role, you will apply advanced Design of Experiments (DoE) and causal inference techniques in real-world, noisy environments where interventions may occur at the branch, customer, or SKU level. You will partner closely with operations, merchandising, pricing, and product teams to ensure experiments are statistically rigorous, operationally feasible, and actionable.
Required Skills & Experience

• 5+ years of experience in data science, experimentation, or statistical modeling
• Deep expertise in Design of Experiments, including:
  • Factorial and fractional factorial designs
  • Response surface methodologies
  • Matched-market testing
  • A/B/n and multivariate experimentation
• Proven experience designing and executing experiments in operational or distribution network environments (e.g., branch- or location-based pilots)
• Strong statistical programming skills in Python or R; proficiency in SQL and modern data platforms
• Hands-on experience applying causal inference methods in real-world, non-laboratory settings

Preferred Skills & Experience

• Advanced degree (M.S. or Ph.D.) in Statistics, Data Science or a related quantitative field

• Background in Operations Research, including optimization, simulation, or queuing theory
• Experience in B2B, industrial distribution, logistics, or supply chain environments
• Familiarity with cloud-based data and compute platforms such as Databricks, Snowflake, AWS, or Azure
• Experience developing standardized experimentation frameworks or playbooks
• Strong executive communication and stakeholder influence skills

What You Will Be Doing

• 35% Experimental Design & Methodology (DoE, matched markets, multivariate testing)
• 25% Measurement, Causal Inference & Impact Quantification
• 20% Operations Research & System-Level Modeling
• 20% Cross-Functional Strategy & Experimentation Enablement

Daily Responsibilities

• Architect and operationalize structured experimental designs across branches, SKUs, and customers to evaluate pricing strategies, stocking decisions, and operational changes
• Design branch-level pilots using matched-market methodologies to ensure clean test/control comparisons and strong causal inference
• Implement advanced DoE frameworks beyond basic A/B testing, including factorial designs and response surface methods
• Develop within-branch experimental designs (e.g., SKU-level treatments with internal controls) to isolate effects in complex operational environments
• Build and maintain robust pilot measurement frameworks, including KPIs, dashboards, and real-time monitoring
• Apply statistical and causal inference techniques such as difference-in-differences, synthetic controls, and regression modeling to quantify results
• Partner with operations, merchandising, pricing, branch leadership, and product teams to identify opportunities, define treatments, and interpret results
• Create standardized DoE playbooks and pilot protocols to scale experimentation across the organization

The Offer

• Competitive Salary + 401(k)
• Health, Dental, Vision Insurance, and Life Insurance
• PTO

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future.

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