Turn real business problems into analytical questions and model designs.
Work with traders, risk managers, finance, digital, and data teams to understand how decisions are made.
Build and test machine learning / statistical / optimization models and evaluate them with robust validation approaches.
Create datasets, explainability outputs, and decision-support products (recommendations, alerts, dashboards, decision cards).
Communicate results clearly, so non-technical stakeholders can trust and act on them.
Typical projects include: regime-shift detection, price sensitivity/hedge analytics, forecasting supply/demand/inventory risk, and explainable tools for decision reviews.

A Bachelor’s or Master’s degree in Data Science, Computer Science/Engineering, Statistics, Mathematics, Engineering, Economics, OR/Quant or similar.
0–2 years’ experience (including internships).
Strong Python + SQL skills, and comfort working with large, imperfect datasets.
Curiosity about Agentic AI, as well as an interest in commodities, trading/risk, supply chains, combined with a motivation to build models people will use.

High exposure + learning velocity : an experiential journey that “tests your initiative, stimulates ambition and creativity, and demands energy and intellect.”
Mentoring & coaching : support from business leaders plus program anchors across L&D/Talent/HR.
Breadth and network: rotate through value-stream exposure and live projects with business impact to build perspective and connections.
A combination (70/20/10) of on-the-job learning, coaching/mentoring and formal training.

Data Science Graduate Program

Key skills