Senior Data Scientist - Supply Chain

Who We Are

We’re Dealer Tire, a family‑owned, international distributor of tires and parts established in 1918 in Cleveland, OH. We’re laser focused on helping the world’s largest and most trusted auto manufacturers grow their tire business—in fact, we’ve sold more than 60 million tires to date. We’re a thriving company, and we’re looking for driven individuals to join our team. That’s where you come in!

Base Pay Range: $130,000-$145,000

• Deliver data-driven insights through advanced algorithms and statistical models aligned with Supply Chain strategy, maximizing profitability and minimizing costs.

• Collaborate with leadership to effectively solve problems, assess results, and communicate actionable recommendations.

• Build relationships with cross‑functional teams to drive progress and adoption of Data Science projects.

• Execute discovery sprints and deep EDA to convert anecdotes into testable hypotheses, KPIs, and use cases across supply chain functions.

• Define and track operational KPIs with model health to tie analytics to service, cost, safety, and cash.

• Translate complex analyses into simple narratives and decision memos leaders can act on, linking findings to economics and operational playbooks.

• Identify and prioritize projects with the most significant returns and develop advanced mathematical and statistical models.

• Design optimization/ML/simulation models and package them to drive day‑to‑day operations and decisions with clear recommendations and “what‑if” scenarios.

• Create high‑quality features and datasets with lineage and quality checks; stand up lightweight feature stores and reusable “EDA fact packs” to accelerate future work.

• Develop, maintain, and optimize models in cloud environments, ensuring business teams can leverage insights with actionable recommendations.

• Collect, cleanse, transform, and curate structured and unstructured data into usable formats for research and analysis.

• Utilize tools like SQL and data APIs to manage data in various storage environments, ensuring privacy and confidentiality.

• Lead projects and collaborate with subject matter experts to align analysis outcomes with organizational goals.

• Partner with MLE / DE to deliver resilient pipelines with alerting, and retraining; author runbooks and guardrails so Ops can operate models confidently.

• Design and product ionize multi‑agent workflows that read from the data lake or warehouse and trigger actions; implement human‑in‑the‑loop review, role‑based guardrails, and observability.

• Design and deliver scalable, integrated software tools and models that balance predictive power, interpretability, and operational risks.

• Manage strategic projects, ensuring clear communication, timely delivery, and appropriate ROI for recommended initiatives.

• MS in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field.

• 4‑5 years of experience implementing optimization, ML, or AI models.

• Effective program management experience with proven results required

• Strong data engineering principles, familiar with technologies to store, query, process, and analyze data.

• Strong programming skills in languages like Python, C/C++, Java, or Go.

• Proven record of product ionizing models in cloud environments, version control, and MLOps.

• Demonstrate in‑depth technical capabilities, professional knowledge and understanding in functional areas of Supply Chain & Optimization – Inventory, Transportation, Sourcing, Distribution, Fulfillment, and Planning.

• 2+ years of practical experience with Optimization + Simulation (Pyomo/OR‑Tools/Gurobi/CPLEX; Monte Carlo/discrete‑event) and ML.

• Ability to simplify complexity, influence cross‑functionally, and tell the story behind the math.

• Displays a creative mindset with problem solving in sophisticated and complex environments. This includes and is not limited to identifying both new and existing problems and applying the most appropriate…