Data Scientist

Advance Stores Company•Raleigh, NC

6d•Hybrid

About The Position

Job Summary: We are seeking a motivated Data Scientist with strong technical skills in machine learning and a passion for continuous learning. The ideal candidate will have foundational experience in building predictive and prescriptive models using Python, PySpark, and modern ML frameworks (TensorFlow, PyTorch, XGBoost, LightGBM). This role requires the ability to write production-ready code, develop automated model monitoring workflows, create visualization dashboards, and work collaboratively in Agile environments with cross-functional teams. This position is 4 days in office, 1 day remote per week, based at our corporate headquarters in Raleigh, North Carolina (North Hills)

Requirements

1+ years of experience in Data Science, Machine Learning, AI/GenAI.
Master’s degree in computer science, Statistics, Operations Research, Mathematics or similar.

Nice To Haves

Familiarity of GenAI and agentic solutions, Retrieval-Augmented Generation (RAG) and model distillation is a plus.
Experience in Retail Industry
AI/ML certifications in Vertex AI/Databricks/AWS.

Responsibilities

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.
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.
Rapidly prototype and test hypotheses to validate model approaches.
Should be a team player and should have a strong desire to learn new technologies and methodologies.
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.