Sr Applied Scientist/Data Scientist _ ALLOCATION OPTIMIZATION _ Remote _ Retail Domain Experience

Title: Sr Applied Scientist / Data Scientist with Demand Forecasting Location: Remote ROLE: SENIOR APPLIED SCIENTIST-DEMAND FORECASTING OVERALL EXPEREINCE 9-10 YRS+ Scope: 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 region

SENIOR APPLIED SCIENTIST-OPERATION RESEARCH & SYSTEMS ANALYST (ORSA)-Retail/Inventory DomainIntroduction: This position involves leading the optimization architecture, problem formulation, solver selection, and constraint modeling in the Retail/Inventory domain for a client in the retail industry. Responsibilities:Lead the optimization architecture: problem formulation, solver selection, constraint modelingOwn the mathematical framework generating optimized allocation plans incorporating busines

Job Title: Sr Applied Scientist - Allocation Optimization | Optimization Engineer Location: Irvine, CA and remote acceptable too Scope: Hands-on mathematical optimization for regional store allocation Extend existing constraint-based, multi-objective allocation framework to new regional store configurations Adapt models to regional business rules (store capacity, presentation minimums, lead times, clearance logic) Model retraining and tuning per region as stores come online Support explainabi

ROLE: SENIOR APPLIED SCIENTIST / Data Scientist - OPERATION RESEARCH & SYSTEMS ANALYST (ORSA) OVERALL EXPERIENCE 9-10YRS+ Scope: Lead the optimization architecture: problem formulation, solver selection, constraint modeling Own the mathematical framework generating optimized allocation plans incorporating business constraints Architect multi-objective optimization balancing in-stock rates, inventory turns, and operational costs Guide the optimization team on problem decomposition and solution a