Senior Data Scientist, Inventory 360 (Operations Research)

At DICK’S Sporting Goods , we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve. If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today! OVERVIEW: Are you a passionate technologist with experience in AI, Machine Learning, Operations Research and Data Science? Are you looking for an opportunity to drive enterprise impact and shape the future of a leading sports retailer with $12B+ in revenue and 800+ physical stores? Do you enjoy working with a highly skilled team of Machine Learning engineers & Scientists, co-creating enterprise grade AI capabilities? We are seeking a Senior Data Scientist – Inventory 360 to lead the development of intelligent decisioning systems that optimize inventory flow and operations and drive exceptional customer experiences. This role sits at the intersection of machine learning, operations research, and enterprise systems — powering decisions that determine how, when, and where we fulfill customer demand. This role requires a subject matter expert with deep experience in traditional machine learning and cutting edge AI with a strong foundation in operations research. You’ll apply advanced modeling techniques to design intelligent decisioning systems that optimize fulfillment operations and elevate the customer experience. Your work will focus on solving complex foreacasting and optimization problems — from assortment planning to purchase order optimization to allocation —using a blend of predictive analytics, simulation, and mathematical programming. JOB PURPOSE As a senior data scientist, you’ll influence the enterprise decisioning landscape by developing models that integrate with high-impact systems across merchandising and inventory planning and pricing optimization. You’ll collaborate with product, engineering, and business leaders to translate operational challenges into solvable data science problems, and help them understand the art of the possible through rigorous experimentation, simulation, and model design. Your work will directly influence delivery speed, order accuracy, and service reliability — ensuring every customer interaction is fast, efficient, and frictionless. RESPONSIBILITIES Develop ML and OR-based models for demand forecasting, assortment planning, purchase order optimization, inventory allocation and price optimization. Apply techniques such as mixed-integer programming, dynamic programming, graph theory, spatial optimization and simulation to solve real-time decisioning problems. Integrate predictive ML models with optimization logic to enable adaptive, data-driven decisions. Build and operationalize decision engines that automate fulfillment decisions across the enterprise. Collaborate with engineering to deploy models into production systems with real-time data pipelines and monitoring. Ensure models are interpretable, auditable, and aligned with business constraints. Combine ML outputs with OR solvers via hybrid decision frameworks, enabling scenario-aware optimization and policy simulation. Ensure robustness and scalability of models by leveraging containerized environments and observability tools Enable real time decisioning by building & incorporating streaming pipelines and supporting low latency inference and optimization. Partner with product and operations to define decision boundaries, constraints, and success metrics. Communicate insights and model performance to technical and nontechnical audiences. Understand latest research in the field of OR and AI to give inputs to enterprise roadmaps to ensure we are on the path to build Best in Class merchandising planning and optimization solution PREFERRED SKILLSET Advanced degree (MS/PhD) in Operations Research, Computer Science, Statistics, or related field. 4+ years of experience in building optimization and ML models in assortment planning, optimization, fulfillment or supply chain domains. OR Techniques: linear/mixed-integer programming, simulation, queuing theory. ML Tools: Python, PyTorch/TensorFlow, scikit-learn. Data & Infra: SQL, Spark, Airflow, cloud platforms (Azure, AWS, GCP). Solid understanding of distributed systems, APIs, and cloud infrastructure (Azure, AWS, or GCP). Familiarity with reinforcement learning or contextual bandits for adaptive decisioning in dynamic environments. Familiarity with graph algorithms and path planning for spatial routing and pick path optimization. Skilled in designing and analyzing A/B tests or switchback experiments for operational models. Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.) Comfortable presenting results to cross functional partners and help them understand technical trade of