About the role
We are looking for a data engineer / data scientist intern to help us ship data products fast. The role covers the entire lifecycle of a data project, from raw data to a live product.
You will work closely with the CTO, the Head of Machine Learning and the whole team, and your work will be used directly by our clients. Tools like Claude Code (Max) let you prototype and ship quickly, moving across the stack as the project demands.
What you will do
- Data engineering: collect, clean and prepare data so it is reliable and ready to use
- Data analysis: turn that data into analyses and metrics that answer real product and client questions
- Deployment: expose your work through back-end capabilities powering our analytics dashboard, and simple front-end interfaces
- Build and improve data pipelines, pre-processing, cleaning, aggregation
- Prototype and ship fast with AI coding tools like Claude Code
Who you are
- Strong basics in Python and SQL
- Comfortable manipulating, cleaning and analyzing data
- You want your work to ship: product impact, not just notebooks
- Organized, curious, ambitious, and you want ownership
- Curious about new dev workflows, especially AI-assisted coding
- Comfortable moving fast in a startup environment with high stakes
The stack
- Front-end: TypeScript, React
- Back-end: TypeScript / Node.js, Python, PostgreSQL
- Infrastructure: AWS, GCP
Practical details
- Start date: as soon as possible (flexible)
- Contract: Internship
- Location: Paris (9th arrondissement)
Why Kleep
Kleep builds the intelligence layer for fashion e-commerce: sizing, discovery and AI imagery that 300+ brands run in production, Givenchy, Lacoste and Victoria Beckham among them. Every product is proven in live A/B tests, not in decks.
We are a small, senior, international team with offices in Paris (9th arrondissement) and, since January 2026, New York. The company is led by its founders: Federico (CEO, previously in venture capital and private equity) and Théophile (CTO, an ENS and Mines Paris engineer who worked in trading and quantitative research at Morgan Stanley and BNP Paribas).
Ownership here is real: ideas are heard, feedback flows both ways, and impact is tangible from day one. We hold a high bar, celebrate together, weekly team drinks, monthly events, annual off-sites, and stay serious about the work, never about ourselves.