Senior Data Scientist, Supply Chain Optimization

Fanatics Collectibles; San Mateo (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Fanatics Commerce seeks a Senior Data Scientist to optimize supply chain and inventory using ML-driven modeling, pricing optimization, and demand forecasting. You will lead cross-functional collaboration to build predictive models, deploy scalable pipelines, and deliver measurable business impact across the fan experience.

Ideal candidates bring 6+ years of experience in predictive analytics, strong Python/SQL skills, and expertise in time series, optimization, and production deployment.

Qualifications

• 6+ years of experience building and deploying predictive models in production or operations.
• Strong Python (Pandas, Scikit-learn, NumPy) and SQL, plus Spark or similar for scalable processing.
• Expertise in time series forecasting (ARIMA, exponential smoothing) and ML approaches (XGBoost, LSTM, DeepAR).
• Experience with discrete optimization (MIP, solvers, genetic algorithms) for pricing/clearance/network design.

Responsibilities

• Partner with cross-functional teams to frame supply chain and inventory problems and translate models into actionable tools.
• Communicate modeling tradeoffs and results to technical and non-technical audiences to drive trust and adoption.
• Mentor juniors and contribute to a collaborative data science culture.
• Own the full model lifecycle from problem framing to deployment and monitoring.

Skills

Predictive modeling

Time series forecasting

Python

SQL

Spark

Discrete optimization

Communication

Education

Bachelor's or Master's in Data Science/CS/Statistics/OR

Tools

Pandas

NumPy

Scikit-learn

XGBoost

LSTM

DeepAR

Job description

Fanatics Commerce seeks a Senior Data Scientist to optimize supply chain and inventory using ML-driven modeling, pricing optimization, and demand forecasting. You will lead cross-functional collaboration to build predictive models, deploy scalable pipelines, and deliver measurable business impact across the fan experience.

Ideal candidates bring 6+ years of experience in predictive analytics, strong Python/SQL skills, and expertise in time series, optimization, and production deployment.