About this role
The Senior Data Scientist - Product role at Legora is based at the Stockholm HQ and suits an analytical professional driven by impact, pace, and raising the bar in an AI-first environment. This position involves turning complex data into actionable decisions by working closely across business functions.
Role Overview
Legora is hiring a Senior Data Scientist for Product to join a centralised team supporting the entire organisation. The role allows practitioners to take questions end-to-end, from shaping metrics and modelling data in dbt to running analyses and providing recommendations. The team operates with an AI-first mindset, focusing on ownership, direct feedback, and high standards.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
About the Company
Legora is an AI-native workspace provider designed alongside legal teams to process thousands of documents rapidly and power end-to-end workflows. Serving over 2,100 customers across more than 80 countries with a scale of over $200M in ARR, the company maintains teams globally across Europe, North America, and APAC. The organisation partners with prominent global performers and maintains a culture centered on ownership, direct feedback, and high standards.
How to Apply
To apply for this position, please visit the official company careers page.
Skills and tech stack
Questions candidates ask
Where is the Senior Data Scientist - Product position located?
The role is located at the Stockholm HQ.
What technical languages and tools are required?
Candidates must have strong proficiency in SQL and Python, alongside a solid grasp of data modelling.
What teams might I be embedded with upon joining?
Depending on strengths and company needs, you could be embedded with Product, Finance & RevOps, Growth & Marketing, or GTM & Customer Success.
What tools are included in the company's tech stack for nice-to-have experience?
Snowflake, dbt, Hex, and Dagster.
Is a specific single background required for this job?
No single profile is required; candidates are expected to excel in at least one area—such as data modelling, experimentation, machine learning, or product analytics—and demonstrate competence across the others.
