- Salary
- €50 – €200
- Location
- Helsinki, Uusimaa
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Product
- Seniority
- Senior
- Experience
- 6+ years
- Source
- Lever
Description
Are you an experienced Data Scientist eager to make a significant impact? We're looking for a Data Scientist to join us and help shape the future of our cutting-edge impact data products.
At Upright, you get to work on a product that actually matters: the world's largest open-access database on company impact, used by 1,000+ institutional investors and corporations to make real capital allocation decisions. We quantify companies' impact from the ground up, based on peer-reviewed science and what companies actually produce and sell. The raw material is their product data, which we collect and classify automatically at scale.
A few things our team has built recently:
- A vertically trained LLM purpose-built for sizing the magnitude of real-world impacts to produce impact estimates that are internally coherent and aligned with scientific consensus. Patent pending on the core training technique (US application 19/629,694, filed March 2026)
- An agentic company-mapping pipeline that ingests messy product descriptions, annual reports, and websites, and produces structured, comparable impact-relevant product sets at the scale of tens of thousands of companies and 150 000+ different products
- An LLM-assisted Double Materiality Assessment engine that automates a process consultants currently charge €50–200k for, with structured outputs, retrieval over peer-reviewed evidence, and a custom eval harness keeping quality measurable.
As a Data Scientist, you'll own larger projects and product areas end-to-end, set technical direction in key areas, mentor others, and ship results that show up directly in how institutional capital flows. Your specific responsibilities will be tailored during the recruitment process to your background, skill level, and interests. If you're ready to grow your career while building a platform that matters and to do it in an AI-forward data science environment, we'd love to hear from you!
