RaceTrac Company Overview

Job Description:

The Director, Enterprise Data Science is a cornerstone leader within the Enterprise Strategic Analytics + Data Science team (ESADS), tasked with driving innovation, data science excellence, and operational success across the organization. This role combines technical depth with strategic vision to deliver cutting-edge solutions in Statistical Data Science and Mathematical Optimization (Operations Research). The Director, Enterprise Data Science collaborates closely with Strategic Analytics Partners (SAPs) to ensure alignment with business objectives, while fostering a culture of excellence and continuous improvement within the data science discipline. Additionally, this role guides and supports their team, providing mentorship on designs and approaches, and partners with the business alongside the SAPs to ensure seamless integration of data science solutions with strategic goals.

Responsibilities:

Scope of Role:Lead the design, development, and delivery of advanced data science solutions that address critical business challenges and opportunities within the ESADS framework.Serve as the primary thought leader for innovation in data science, driving the adoption of cutting-edge methodologies, tools, and best practices.Build and maintain strong partnerships with Strategic Analytics Partners to align technical solutions with strategic business priorities and deliver measurable impact.Guide and mentor the data science team, ensuring high-quality designs, approaches, and delivery of solutions.Partner with the business alongside Strategic Analytics Partners to ensure alignment and integration of data science solutions with broader business objectives.Champion the use of AI/ML and optimization techniques, ensuring their application delivers scalable, repeatable, and high-value outcomes.Day-to-Day Activities:Oversee the end-to-end lifecycle of data science projects, from ideation and prototyping to production and monitoring.Collaborate with cross-functional teams to identify opportunities for leveraging data science to create business value.Conduct rigorous reviews of statistical and optimization models to ensure they meet business needs, technical standards, and ethical guidelines.Mentor and develop a high-performing data science team, fostering technical expertise, innovation, and career growth.Represent ESADS in high-visibility meetings and presentations with executive leaders to communicate progress, insights, and strategic recommendations.Be a vocal and visible leader in our AI Education, Innovation, and Governance team.Expected Outcomes:Deliver transformative data science solutions that enhance decision-making, operational efficiency, and competitive advantage.Elevate the analytical maturity of the organization by integrating predictive and prescriptive analytics into business processes.Demonstrate measurable impact through successful implementation of advanced data science initiatives, with impact explicitly measured in terms of ROI, that align with ESADS’ value-driven objectives.Complexities:Navigate highly complex and ambiguous problems, balancing technical depth with strategic alignment to meet organizational goals.Manage competing priorities across multiple projects while ensuring adherence to timelines, budgets, and quality standards.Manage competing priorities across multiple projects while ensuring adherence to timelines, budgets, and quality standards.Maintain a dual focus on fostering innovation and ensuring operational excellence in the delivery of data science solutions.

Qualifications:

Required Experience:Master’s or PhD in Data Science, Operations Research, Applied Mathematics, Computer Science, or a related field.Minimum of 10+ years of experience in data science roles, with a proven track record of delivering high-impact solutions in Statistical Data Science and Mathematical Optimization.Extensive experience with AI/ML technologies, optimization algorithms, and large-scale data processing frameworks.Demonstrated expertise in tools such as Python, R, SQL, Databricks, and visualization platforms like Tableau or Power BI.Significant experience working in cross-functional teams and influencing stakeholders at all levels of the organization.Demonstrable experience with one or many of the following: Demand Forecasting, Flexible Segmentation (Customer, Performance, Weather, etc.), Network Optimization, Predictive Maintenance/Service, Predictive Customer Churn, Price Optimization, Risk Modeling, Marketing Mix Modeling, Customer Journey Analytics, Predictive Staffing Optimization, Staff Attrition/Retention Risk, Next Best Product/Offer, Customer Elasticity (Market Response Modeling), Assortment Optimization, Customer Loyalty Effectiveness/OptimizationBeneficial Experience:Previous leadership experience managing data science teams and projects in enterprise environments.Consulting experience in analytics-driven industries, such as retail, logistics, or financial services.Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud, Palantir) and MLOps best practices.

All qualified applicants will receive consideration for employment with RaceTrac without regard to their race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.