Senior Applied Scientist - Demand Forecasting

Prodapt

$130K — $155K *
Retail & Consumer Goods
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Applied statistics and time-series forecasting expertise (ARIMA, Prophet, neural methods)
  • Experience in retail demand planning or demand sensing
  • Proficient in SageMaker model training and deployment
  • Strong programming skills in Python and SQL, with large-scale retail datasets
  • Bachelor's degree in Computer Science, Engineering, or related field; OR equivalent experience
  • 7+ years as an Applied Scientist focused on demand forecasting
  • Ability to work independently with architectural direction

Responsibilities

  • Develop and retrain demand forecasting models for new regional markets
  • Adapt forecasting framework to reflect regional demand signals
  • Calibrate forecast accuracy using federated regional data
  • Validate model quality to meet go-live thresholds for regional activation
  • Collaborate with the optimization team for allocation engine inputs

Benefits

  • Opportunity to work with cutting-edge machine learning technologies
  • Engagement in a high-impact role influencing regional market strategies
  • Collaborative work environment with cross-functional teams
  • Professional development opportunities in forecasting methodologies
  • Impactful contributions to supply chain and retail analytics
Full Job Description
Overview

We are seeking a highly skilled Senior Applied Scientist with expertise in demand forecasting, machine learning, and retail analytics to develop and optimize forecasting models at scale.

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


Requirements

  • 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 a related field; OR equivalent combination of education and relevant experience.
  • Hands-on 7+ years of experience asApplied Scientist with expertise in demand forecasting.
  • Ability to work independently with architectural direction from lead scientist

Preferred:
  • Supply chain or inventory management domain experience
  • Multi-market / international retail exposure

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