> Markdown version of [/jobs/ext/2786845-product-analytics-data-science](https://www.wearedevelopers.com/jobs/ext/2786845-product-analytics-data-science). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Product Analytics & Data Science - **Company:** We're Criteo - **Location:** France - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, Big Data, Encodings, Python (Programming Language), Search Technologies, SQL Databases, Large Language Models, Information Technology, Data Pipelines - **Published:** September 8, 2026 - **Apply:** https://startup.jobs/product-data-science-ai-agents-intern-criteo-com-9945737 ## About the Role * Master's degree student or higher (Mathematics, Computer Science, Physics, Engineering, Economics, etc.) * Available for at least 5 to 6 months from January 2027. * End of study or gap year internship * Outstanding analytical skills, creative thinking, and a builder's mindset - you like to prototype, not just analyze * Fluency in the core toolkit of Data Science: Python; SQL; manipulating large-scale data sets; building data pipelines; descriptive and predictive modeling; implementing visualizations, dashboards and reports * Curiosity and ideally hands-on experience (through projects, coursework or personal tinkering) with the AI-native toolkit: LLMs and prompting, building agents or skills, retrieval / embeddings, or agent evaluation - or a strong eagerness to learn these fast * Excellent interpersonal and communication skills, pro-active and independent to work with! PS: Please apply with an English resume ## Description You will be assigned to one or several projects. The topics we tackle are wide and always evolving. Recent examples of the AI-native, agentic work you could contribute to: * Build AI agents & skills for the team - design agents that automate recurring analytical work (e.g. a reporting agent, a Slack assistant, an AI skill), and ship them into our shared skills registry so the whole team benefits. * Agent evaluation & guardrails - help build frameworks that evaluate multi-turn agents (LLM-driven personas talk to a real agent, LLM judges score relevance, coherence, helpfulness, safety and accuracy), so agentic products ship faster and more safely. * Product intelligence prototypes - build retrieval / embedding-based systems for product understanding (e.g. semantic search over publisher content for supply discovery, brand safety, or audience creation). * LLM-powered diagnostics at scale - use LLMs to detect, sample and route quality issues across complex product pipelines (e.g. tracing where a catalog signal is lost and who should fix it). * Messy, cross-functional product problems - jump into ambiguous product and client challenges (identity, measurement, trading, creative validation) and use fast prototyping and AI tooling to converge on solutions that work in the real world. Overall, your responsibilities include: * Design, build and evaluate AI agents and reusable skills that solve real product and analytical problems * Support the team in framing product and client problems early with PM, R&D, GTM and Design - then prototype narrow, high-value solutions quickly * Build evaluators, guardrails and golden-dataset tests so the systems you ship are trustworthy * Turn repetitive manual tasks into trusted agents that scale beyond you * Mine large data sets and turn them into understandable and actionable insights * Master our internal analytic datasets, tooling and AI stack ## Related Videos - [Recruiting in 2025: Will AI Help or Take Over?](https://www.wearedevelopers.com/videos/1301-recruiting-in-2025-will-ai-help-or-take-over) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [AI, DEI & Community: What’s Next for Talent Acquisition in 2025?](https://www.wearedevelopers.com/videos/1315-ai-dei-community-what-s-next-for-talent-acquisition-in-2025) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Jobs in Tech: The State of the European Market](https://www.wearedevelopers.com/magazine/575-jobs-in-tech-the-state-of-the-european-market) - [Best Companies to Work For in Paris: Top 25 Companies in 2023 ](https://www.wearedevelopers.com/magazine/190-best-companies-to-work-for-in-paris-top-25-companies-in-2023) - [Best Coding Boot Camps in Germany](https://www.wearedevelopers.com/magazine/237-best-coding-boot-camps-in-germany) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)