Data Scientist

About the Role

Come join our Technology Team and start reimagining the future of the automotive aftermarket. We are a highly motivated tech-focused organization, excited to be amid dynamic innovation and transformational change. Driven by Advance’s top-down commitment to empowering our team members, we are focused on delighting our Customers with Care and Speed, through delivery of world class technology solutions and products. We value and cultivate our culture by seeking to always be collaborative, intellectually curious, fun, open, and diverse. You will be a key member of a growing and passionate group focused on collaborating across business and technology resources to drive forward key programs and projects building enterprise capabilities across Advance Auto Parts.

Key Responsibilities

Model Development & Technical Expertise

• Design and implement predictive and prescriptive models for regression, classification, and optimization problems.
• Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM).
• Develop and tune machine learning models using Python, PySpark, TensorFlow, and PyTorch.
• Write efficient, production-ready code and frameworks optimized for scalability and deployment.
• Familiarity of GenAI and agentic solutions, Retrieval-Augmented Generation (RAG) and model distillation is a plus.

Collaboration & Communication

• Work closely with stakeholders to understand business challenges and translate them into data science solutions and work in the end-to-end solutioning.
• Collaborate with cross-functional teams to ensure successful integration of models into business processes.

Monitoring & Visualization

• Rapidly prototype and test hypotheses to validate model approaches.
• Build automated workflows for model monitoring and performance evaluation.
• Create dashboards using tools like Databricks and Palantir to visualize key model metrics like model drift, shapley values etc.

Agile Execution

• Operate effectively in Agile environments, contributing to iterative development cycles and sprint planning.
• Adapt quickly to changing priorities while maintaining high standards of quality and innovation.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.