Refineries Analyst

About the Company

Kpler helps organisations make sense of complex markets by turning global trade information into practical insight. Its work supports decision-making across commodities, energy, and maritime sectors. Founded in 2014, the company provides intelligence through easy-to-use platforms and is powered by a team of more than 700 specialists from over 35 countries.

Role Overview

Kpler’s Oil & Chemicals team is expanding its real-time analytics capability and is hiring a technically strong, data-focused Refineries Analyst. This role is centred on safeguarding the accuracy, upkeep, and quality of bottom-up refinery models. You will combine proprietary live market inputs such as crude flows, production, pipeline volumes, and inventory data into a structured modelling environment, using the internal Linear Programming model to support tuning and optimisation.

You will connect upstream market inputs and offline events with refinery capacities and yields, ensuring the models align with Kpler’s broader supply and demand balances. As the platform grows, you will help shape core product functionality and work closely with Product Engineering as a subject matter expert linking physical refinery realities with technical system design.

Key Work Areas

• Keep refinery model data accurate, including capacity details and offline event records, across individual assets and regional balances, while using the internal LP model for tuning.
• Focus on strengthening existing models by improving data quality and applying strong domain knowledge.
• Use outside benchmarks and reference sources such as EIA, JODI, IRR, and ANP to backtest models and ensure outputs reflect real market conditions.
• Apply expertise in distillation, reforming, FCC, and blending to improve refinery circuit views and regional supply-demand modelling.
• Use Python and PostgreSQL to work with large datasets, automate data processes, and improve model reliability.
• Partner with Data, Product, Engineering, and Sales teams to support refinery product development with analysis and insight.
• Handle internal and external data requests and client questions promptly and professionally.

Experience and Technical Requirements

The role calls for at least 3 to 5 years of experience in refinery economics, refinery analysis, LP modelling, or a closely related field. Hands-on familiarity with industry LP software such as Aspen PIMS, AVEVA Unified/Spiral, or Haverly GRTMPS is required to be effective in the position.

You should also be comfortable working with Python and PostgreSQL, and have practical experience using external datasets like EIA, JODI, or IRR for refinery modelling. Strong capability in data-driven modelling, validation, and maintaining input-data integrity, including capacity and offline event records, is essential.

Preferred Experience

• Exposure to refinery optimisation with a circuit-wide perspective.
• Experience with data visualisation.
• Previous contribution to SaaS product development or data enhancement projects.
• Use of AI tools such as Claude or Cursor for analysis, data handling, or workflow improvement.

Behavioural Expectations

• Strong ownership of daily responsibilities and careful attention to detail.
• Ability to work independently in a fast-moving, early-stage product environment.
• Willingness to spend significant time refining individual refinery models and bottom-up structures.
• Motivation to find and apply data that improves backtesting and model guidance.
• Confidence in client-facing communication.

Education

A bachelor’s degree in a technical or quantitative discipline is required, along with demonstrated use of modelling techniques in commercial or research settings.

Company Values

• We make things happen: The team acts decisively, stays purposeful, and goes the extra mile.
• We build together: Collaboration and creative problem-solving are encouraged to address market challenges.
• We are here to help: The company values a supportive, accessible, and friendly approach with colleagues and clients.

Inclusion Statement

Kpler encourages applicants from all backgrounds and wants candidates not to be discouraged if they do not meet every requirement. The company is committed to an inclusive, diverse, and fair workplace and welcomes different perspectives, abilities, and experiences.

Hiring Process Note

Artificial intelligence tools may be used to assist with parts of the recruitment process, such as application review, resume analysis, or response assessment. These tools support the recruitment team and do not replace human decision-making. Final hiring choices are made by people.