Refineries Analyst

Kpler's Oil & Chemicals business unit is rapidly advancing its real-time analytics and is looking for a technically sharp, data‑literate Refineries Analyst to join its growing global team.

• Take absolute ownership of data integrity, maintenance, and quality control for bottom‑up refinery models.
• Maintain data integrity, capacity, and offline event records for individual refinery models and regional balances using the internal Linear Programming model for tuning.
• Prioritize the validation and improvement of existing models.
• Lead the effort to backtest and guide models using external data sources such as EIA, JODI, IRR, and ANP to ensure outputs align with physical market realities.
• Apply a deep understanding of distillation, reforming, FCC, and blending to optimize refinery circuit views and regional supply‑demand dynamics.
• Source and leverage large datasets using Python, Postgre
  
  SQL, and related tools to automate data flows and improve model accuracy.
• Collaborate with Data, Product, Engineering, and Sales teams to provide insights for refinery product development.
• Respond to internal and external data requests and client queries in a timely manner.

• At least 3–5 years of experience as a Refinery Economist, Refining Analyst, LP Modeler, or related role.
• Deep understanding of physical refinery unit operations (distillation, reforming, FCC, blending, etc.) and refinery economics (flows, pricing, regulations, and arbitrage dynamics).
• Practical experience using industry‑standard Linear Programming software (Aspen PIMS, AVEVA Unified/Spiral, or Haverly GRTMPS).
• Comfortable with Python and Postgre
  
  SQL.
• Proven experience sourcing and leveraging external data (EIA, JODI, IRR) to model refineries.
• Strong background in data‑driven modeling, validation, and managing input data integrity (e.g., capacity and offline events).

• Experience with refinery optimization, especially with a focus on circuit‑wide views.
• Experience with data visualization.
• Past experience contributing to SaaS product or data improvement initiatives.
• Experience leveraging AI tools (Claude, Cursor, etc.) for data analysis & management and general workflow optimization.

• Ownership of day‑to‑day work and strong attention to detail.
• Self‑starter who thrives in an ambitious, early‑stage product environment without requiring direct supervision.
• Eagerness to invest significant time in individual refinery tuning and bottom‑up modeling.
• Driven to find data to backtest and guide models.
• Client‑facing confidence.

• Bachelor's degree in a technical or quantitative field, with proven experience applying modeling techniques in commercial or research environments.