Senior Applied Scientist - Global Retail Demand Forecasting

Prodapt; San Jose (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Prodapt is seeking a Senior Applied Scientist with expertise in demand forecasting, machine learning, and retail analytics to develop forecasting models at scale. You will work on regional markets, adapt forecasting frameworks to seasonality and lead times, and calibrate accuracy with federated data.

Collaborate with the optimization team and validate models against go-live thresholds before activation. Strong Python/SageMaker skills and 7+ years of experience are required.

Qualifications

• Applied statistics, time-series forecasting (ARIMA, Prophet, neural methods).
• Retail demand planning or demand sensing experience.
• SageMaker model training and deployment.
• Python, SQL, experience with large-scale retail datasets.
• Bachelor’s degree in Computer Science, Engineering, or related field; 7+ years of experience as Applied Scientist.

Responsibilities

• Develop and retrain demand forecasting models for new regional markets.
• Adapt forecasting framework to regional signals (seasonality, buying patterns, lead times).
• Calibrate forecast accuracy using federated regional data.
• Validate model quality meets go-live thresholds before activation.
• Collaborate with the optimization team on inputs to the allocation engine.

Skills

Forecasting

Time-series forecasting

ML models

Education

Bachelor's degree in CS/Engineering

Tools

SageMaker

Python

SQL

Job description

Prodapt is seeking a Senior Applied Scientist with expertise in demand forecasting, machine learning, and retail analytics to develop forecasting models at scale. You will work on regional markets, adapt forecasting frameworks to seasonality and lead times, and calibrate accuracy with federated data.

Collaborate with the optimization team and validate models against go-live thresholds before activation. Strong Python/SageMaker skills and 7+ years of experience are required.