Data Scientist — Churn & Revenue Growth (Hybrid)

Planet Paymet; Greater London; Hybrid; GBP 85,000 - 110,000; Full time

Benefits offered by this job

Hybrid work model

Reasonable accommodations

Job summary

Planet seeks a Data Scientist to join its AI team on a long-term fixed-term contract, hybrid in-office in London with optional collaboration across Porto and Warsaw. You will lead commercial data science to reduce churn, surface cross-sell opportunities, and provide a clear view of revenue drivers.

Strong SQL/Python and production experience are essential. The role involves partnering with Sales, Marketing, Customer Success, and Finance, designing attribution frameworks, and deploying models to

Qualifications

• 5+ years in applied data science focusing on commercial problems (churn, LTV, propensity, attribution, pricing, or similar).
• Strong SQL and Python (pandas, scikit-learn, statsmodels).
• Experience with Snowflake or similar cloud data warehouse and deploying models on AWS.
• Solid statistics, experimentation, and causal inference grounding.
• Track record of shipping models used by the business, not just built.

Responsibilities

• Churn modelling — Build, deploy, and iterate on churn prediction models and indicators.
• Cross-sell & upsell — Develop propensity models and next-best-action recommendations.
• Revenue attribution & tracking — Design attribution frameworks across channels and product touchpoints.
• Experimentation — Design and analyse A/B tests with rigorous statistical methods.
• Productionisation — Take models from notebook to production with end-to-end lifecycle.

Skills

SQL

Python

Snowflake

AWS SageMaker

Statistics

Tools

Airflow

DBT

Dagster

Job description

Planet seeks a Data Scientist to join its AI team on a long-term fixed-term contract, hybrid in-office in London with optional collaboration across Porto and Warsaw. You will lead commercial data science to reduce churn, surface cross-sell opportunities, and provide a clear view of revenue drivers.

Strong SQL/Python and production experience are essential. The role involves partnering with Sales, Marketing, Customer Success, and Finance, designing attribution frameworks, and deploying models to