Principal Data Scientist

Role Overview

• Lead the design and delivery of advanced optimization, machine learning, and decisioning solutions for high-value retail and supply chain problems, including replenishment, placement, inventory flow, and fulfillment planning.
• Shape the technical roadmap for systems such as replenishment override agents, allocation and placement engines, item exit optimization, fit-to-shelf logic, and demand-splitting workflows.
• Build and productionize scalable models and algorithms that operate across large datasets, complex business constraints, and network-level decisions spanning stores, DCs, and fulfillment centers.
• Partner with product managers, engineers, and business stakeholders to define problem statements, success metrics, experimentation approaches, and production roll-out strategies.
• Translate ambiguous operational challenges into mathematically rigorous and implementable solutions, including optimization formulations, heuristics, simulations, predictive models, and decision-support tools.
• Drive architectural decisions for production-grade science systems using modern cloud and distributed data platforms.
• Set a high technical bar through code quality, validation strategies, experimentation discipline, observability, and safe deployment practices.
• Mentor senior and junior data scientists, provide technical guidance across projects, and help scale reusable science patterns, frameworks, and best practices across the team.
• Communicate findings, tradeoffs, and business impact clearly to leaders across science, engineering, and operations.
• Identify innovation opportunities that can translate into patents, reusable platforms, and step-change business outcomes.

Requirements

• Masters or PhD with > 10 years in Computer Science, Statistics, Mathematics, Operations Research, Economics, Engineering, or related quantitative field and 8+ years of experience in data science, machine learning, optimization, or related field.
• Experience leading complex technical initiatives from problem framing through production deployment and business adoption.
• Experience working with Python and modern data/science tooling in cloud or distributed computing environments.
• Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
• Option 2: Masters 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.

Tech Stack

• Cloud
• Python

Benefits

• Health insurance
• Professional development opportunities