Product Analyst Intern – Price & Transaction

About the role

Price & Transaction is Kpler’s newest team. We add commodity prices to Kpler’s market data, and our main product, Kpler Arbitrage, answers one question: does it pay to ship a cargo from A to B? Is the price gap big enough to cover freight, losses, financing and quality differences?

As a 6-month end-of-study intern in Paris, you’ll work next to our Trading Analysts, Product Managers & Engineers. You’ll run modelling studies, test new features and releases, build data-quality dashboards, and learn how physical trading works along the way.

Key Responsibilities

• Run modelling studies. Take part in data-science-style studies on our arbitrage models: test hypotheses, compare model outputs with market data, and present what you find and what it means for the product.
• Learn the business. Learn how price benchmarks, freight and quality differences combine into an arbitrage by checking the numbers our models produce. Trading Analysts explain the market logic, and you work day to day with them & engineers.
• Support the roadmap. Help our senior product team collect inputs from analysts and clients, document and size requests, and keep the backlog clear and prioritised.
• Test new features and releases. Write test cases, check outputs against what the market actually does, and log bugs and feedback with clear examples and expected behaviour.
• Build reliability dashboards that last. Design and set up dashboards tracking the freshness, coverage and quality of our price and arbitrage data, with alerts on outliers and gaps. You document them so the team can maintain them long after your internship.
• Help on data batches. Support our data batches (mappings, route and price updates): follow QA checklists, validate results before they go out, and flag anomalies early.

Experience & Background

You don't need to know it all yet. We'll teach you the market and the product. What we want is curiosity, rigour, enthusiasm for data and an interest in commodity markets.

Essential:

• Final-year student: Currently completing a Master’s degree or Grande École diploma in Engineering, Finance, Data, or an applied quantitative field, available for a 6-month end-of-study placement.
• Data-fluent: Proficient in extracting and analyzing data with SQL and/or Python, transforming raw numbers into intuitive, actionable visualizations and structured tables.
• Quality-minded: Methodical in auditing data integrity-consistently spotting anomalies or calculation gaps, applying verification checklists, and taking pride in thorough, high-quality deliverables.
• Smart with AI: Comfortable integrating AI tools into your daily workflow to move faster, while maintaining total accountability for verifying logic and verifying outputs before sharing.
• A proactive communicator: Fluent in English, comfortable working in an international team, and skilled at writing crisp, structured updates and technical bug reports.

Nice-to-haves:

• Academic coursework or project experience in statistical modeling, quantitative finance, or econometrics.
• Foundational understanding of commodity markets, physical trade flows, or trading economics.