Data Scientist

• Design and analyse experiments across product, growth and retention surfaces
• Build models and analyses that influence real roadmap and GTM decisions
• Work hands-on in Python (Pandas, NumPy, scikit-learn), SQL and notebook environments (Jupyter, Hex)
• Build and maintain analytical layers in dbt against a warehouse (Snowflake, BigQuery or DuckDB-style stack)
• Partner with product and engineering on event instrumentation and tracking plans
• Use AI tooling (Claude, Cursor and similar) across every part of your analytical workflow to compress cycle time
• Present findings clearly to founders and stakeholders, with sharp written and verbal communication

• Strong Python and SQL for day-to-day analytical work
• Solid experience with experimentation, causal inference or statistical modelling in a product environment
• Comfortable with dbt and a modern warehouse (Snowflake, BigQuery, Databricks or similar)
• Fluent with Pandas, NumPy, scikit-learn and notebook tools like Jupyter or Hex
• Fluent in modern AI tooling (Claude, Cursor, ChatGPT) and able to use it to materially raise your output
• High autonomy, strong communication, pragmatic approach to messy early-stage data
• Happy working 5 days a week in-person with a small, high-intensity team

Nice to have:

• Prior early-stage startup experience with no formal data team to lean on
• Exposure to LLM evals, user behaviour modelling on AI products or agent telemetry
• Comfort shipping lightweight production code when the analysis needs to live somewhere