Senior Demand Forecasting Scientist - Retail & Multi-Market

Prodapt Solutions Private Limited; San Jose (CA); On-site; USD 170,000 - 230,000; Full time

Job summary

Prodapt Solutions Private Limited in San Jose, CA, is seeking a Senior Applied Scientist to design and optimize forecasting models at scale for regional markets, leveraging advanced statistics and retail analytics.

You will develop and retrain demand forecasting models (ARIMA, Prophet, neural methods), adapt the forecasting framework to regional signals (seasonality, buying patterns, lead times), calibrate accuracy, validate go-live thresholds, and collaborate with the optimization team on

Qualifications

• Bachelor's degree in CS/Engineering or related field, or equivalent experience.
• 7+ years as Applied Scientist in demand forecasting.
• Experience with regional forecasting and multi-market data.

Responsibilities

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

Skills

Applied statistics

Time-series forecasting

Retail demand planning

Independent work

Education

Bachelor's degree in Computer Science, Engineering, or related field

Or equivalent combination of education and relevant experience

Tools

SageMaker

Python

SQL

Job description

Prodapt Solutions Private Limited in San Jose, CA, is seeking a Senior Applied Scientist to design and optimize forecasting models at scale for regional markets, leveraging advanced statistics and retail analytics.

You will develop and retrain demand forecasting models (ARIMA, Prophet, neural methods), adapt the forecasting framework to regional signals (seasonality, buying patterns, lead times), calibrate accuracy, validate go-live thresholds, and collaborate with the optimization team on