Senior Data Scientist at Advance Auto Parts

Raleigh, North Carolina, United States

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Automotive, RetailIndustries

5+ years of experience in Data Science, Machine Learning, AI/GenAI
Master’s degree in Computer Science, Statistics, Operations Research or similar
Deep expertise in machine learning model development and production deployment, particularly in predictive and prescriptive analytics
Strong technical background in Python, PySpark, TensorFlow/PyTorch
Expertise in advanced ML algorithms (XGBoost, LightGBM, structural time series)
Experience building scalable AI/ML architectures using platforms like Databricks and cloud services
Strong collaboration and mentoring capabilities
Ability to translate ambiguous business challenges into end-to-end data science solutions
Experience working with cross-functional stakeholders
Ability to guide junior team members through Agile development cycles
Preferred: Experience in Retail Industry
Preferred: AI/ML certifications in Vertex AI/Databricks/AWS
Preferred: 1+ years of experience as team lead
Preferred: Familiarity with GenAI and agentic solutions, Retrieval-Augmented Generation (RAG), and model distillation

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
Create robust and scalable AI/ML frameworks and architectures
Work closely with stakeholders to understand business challenges and translate vague business requirements into data science solutions
Collaborate with cross-functional teams to ensure successful integration of models into business processes
Mentor and provide guidance to junior team members
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 (e.g., model drift, Shapley values)
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