Lead Data Scientist

Own end-to-end design, testing, deployment, and communication of analytical and forecasting models for demand planning, revenue management, and commercial planning.

Analyze and improve production forecasting systems to enhance accuracy, including diagnosing errors and tuning model parameters while ensuring system stability.

Guide and oversee junior data scientists to align technical execution and maintain coding standards within projects involving clients and cross-functional teams.

5+ years experience in Data Science and Analytics; experience with time series forecasting is preferred.

Master’s Degree in Operations Research, Mathematics, Science, Engineering, Business Administration, Business Analytics, Computer Science, or related fields including Supply Chain Engineering.

Strong programming skills in Python/Pyspark; deep knowledge of statistical and machine learning algorithms, especially time series forecasting (exponential smoothing, ARIMA, prophet).

Experience applying analytical methods in supply chain and planning domains such as demand/supply planning, price optimization, and market intelligence.

Experienced operating in supply chain and demand forecasting environments with proficiency in building scalable ML frameworks for demand sensing and price optimization.

Able to communicate complex analytical and forecasting methodologies clearly to non-technical stakeholders and defend model assumptions and outputs.

Capable of leading and mentoring junior data scientists while collaborating successfully across clients, project managers, solution architects, and data engineers.