Role Summary

The Specialist Data Scientist supports the scenario planning team by executing simulations, running scenario experiments, managing data pipelines, and producing reliable risk dashboards. This role is essential for maintaining operational cadence and ensuring accurate inputs for higher-level modeling.

Key Responsibilities

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.

Required Skills & Experience

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, joins, schema checks).

Strong communication and stakeholder management skills.

Preferred Experience

Experience in supply chain, demand/supply planning, or operations analytics.

Exposure to simulation, empirical distributions, or optimization.

Experience with visualization tools (Power BI, Matplotlib, Seaborn, Plotly).