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 60 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 60 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. Youll 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 60 from assortment planning to purchase order optimization to allocation 60using a blend of predictive analytics, simulation, and mathematical programming.

JOB PURPOSE

As a senior data scientist, youll influence the enterprise decisioning landscape by developing models that integrate with high-impact systems across merchandising and inventory planning and pricing optimization. Youll 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 60 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 offs

• Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery.

• Experience with real-time decisioning systems and streaming data architectures.

• Familiarity with reinforcement learning or hybrid ML-OR frameworks.

• Background in eCommerce, retail, or customer-facing fulfillment systems.

• Strong understanding of experimentation design and causal inference.

QUALIFICATIONS:

• Education: Bachelors Degree or equivalent level preferred

• General Experience: Experience enables job holder to deal with the majority of situations and to advise others (Over 3 years to 6 years)

• Managerial Experience: Basic experience of coordinating the work of others (4 to 6 months)

VIRTUAL REQUIREMENTS:

At DICKS, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools(like ChatGPT or others) during interviews or assessments.

To ensure a smooth and secure experience, please note the following:

• Cameras must be onduring all virtual interviews.

• AI tools are not permittedto be used by the candidateduring any part of the interview process.

• Offers are contingent upon a satisfactory background check which may include ID verification.

If you have any questions or need accommodations, were here to help. Thanks for helping us keep the process fair and secure for everyone!