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This is a 6-month internship starting in June/July 2026. You'll participate in team rituals, gain autonomy quickly, and have the opportunity to present your work regularly to management, offering strong visibility within the organization. You'll join the Product team within Mirakl Platform, working on key pillars including Financial Services, Catalog and Order Management.
Job Responsibility:
Drive data analysis initiatives: Define problems, prepare and preprocess data, conduct statistical analyses, and validate results to support product decisions
Quantify the impact of product releases: Measure and analyze the impact of new features and algorithmic changes through before/after analysis, sizing, hypothesis testing, and segmentation
Build and maintain performance dashboards: Create and maintain dashboards for your pillar and squads to track functional adoption and key performance indicators, including shared dashboards with Customer Success and Sales teams
Support the Senior Product Manager: Accompany product development end-to-end from discovery and ideation through delivery and go-to-market
Automate and build internal AI-powered tools: Create tools to facilitate team collaboration and automate recurring tasks, such as specialized support agents for PSP switch projects, product Q&A agents, and benchmarking tools specific to your functional scope
Requirements:
Currently pursuing a gap year internship, end-of-studies internship
Strong analytical mindset with rigorous problem definition, logical reasoning, and structured thinking
Solid foundation in statistics including hypothesis testing, confidence intervals, and methodological choices for before/after impact analysis and group comparisons
Strong SQL skills for data extraction and analysis
Very good level of English required (written and spoken)
Nice to have:
Python experience is a plus
Familiarity with a BI tool (Metabase or equivalent) and data visualization best practices is a plus
Basic knowledge in exploratory data analysis and preprocessing (data cleaning, normalization, outlier management) is a plus
Ability to use AI tools critically - explaining, challenging, and correcting AI outputs