Product Analyst Intern – Price & Transaction

Kpler

. Run modelling studies on arbitrage models, test hypotheses, compare model outputs with market data, and present findings and product implications .

Posted 11/9/2026internshipParis • FranceEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in data extraction and analysis using SQL and Python, with a strong ability to create actionable visualizations and structured tables. Experienced in auditing data integrity, applying verification checklists, and documenting technical findings in a collaborative, international environment.

Highest-signal resume keywords

SQL Data AnalysisPython ProgrammingStatistical ModelingData VisualizationCommodity Markets Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ExtractionData AnalysisStatistical ModelingData Integrity AuditingTest Case WritingDashboard DesignBug ReportingMarket Data ComparisonHypothesis TestingData Mapping

Soft Skills

Methodical ApproachClear CommunicationTeam CollaborationAttention to DetailAdaptability

Tools & Technologies

AI ToolsData Dashboards

Industry Keywords

Commodity MarketsQuantitative FinanceTrading EconomicsPhysical Trade FlowsFreight Analysis

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Run modelling studies on arbitrage models, test hypotheses, compare model outputs with market data, and present findings and product implications
Learn how price benchmarks, freight, and quality differences combine into arbitrage
Work with Trading Analysts and Engineers on market logic and product development
Help the senior product team collect analyst and client inputs, document and size requests, and prioritize the backlog
Write test cases, test new features and releases, compare outputs with market behavior, and log bugs with clear examples
Design and set up dashboards tracking freshness, coverage, and quality of price and arbitrage data
Add alerts for outliers and data gaps and document dashboards for ongoing maintenance
Support data batches including mappings, route updates, and price updates
Follow QA checklists, validate results before release, and flag anomalies

Requirements

What you’ll need

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
Proficient in extracting and analyzing data with SQL and/or Python
Able to transform raw numbers into intuitive, actionable visualizations and structured tables
Methodical in auditing data integrity and spotting anomalies or calculation gaps
Able to apply verification checklists and deliver thorough, high-quality work
Comfortable integrating AI tools into daily workflows while verifying logic and outputs
Fluent in English
Comfortable working in an international team
Skilled at writing crisp, structured updates and technical bug reports
Interest in commodity markets
Nice-to-have: coursework or project experience in statistical modeling, quantitative finance, or econometrics
Nice-to-have: foundational understanding of commodity markets, physical trade flows, or trading economics

Benefits

Comp & perks

Equal opportunity employer
Fair, inclusive and diverse work environment
Supportive and accessible colleagues and clients
Learning opportunities alongside Trading Analysts, Product Managers, and Engineers