Data Scientist

Run daily/weekly/monthly scenario analyses (shock modeling, lead-time variability, bias/drift detection). Produce forecast cones, velocity assessments, scenario comparison charts, and risk heatmaps. Perform data prep, feature engineering, cleansing, and schema validation. Maintain modeling configs, parameter files, and version control. Support simulation model improvements via testing, QA, and benchmarking. Collaborate with planners to interpret outputs and prepare business presentations. Monitor performance of scenario engines; flag anomalies or broken logic. Document modeling workflows, assumptions, and data dependencies. 2-6 years in Data Science, Analytics, or Quantitative Modeling. Strong analytical foundation with Python (Pandas, NumPy) and basic modeling experience. Knowledge of forecasting concepts, basic simulation, statistical modeling, and data QA. Ability to interpret model outputs and translate them into clear action points. Solid data engineering fundamentals (pipelines, ...