Lead Data Scientist - Personalisation/CRM

Requirements:

• You have expert knowledge of Python and are able to make and justify design decisions in your code (packaging, testing, config-driven pipelines).
• You have expert knowledge of SQL and can write, debug and optimize complex queries against a warehouse.
• You have hands-on experience shipping and operating predictive ML models or recommendation systems in production (classification / propensity / churn / next-best-action) — end-to-end from feature pipelines (SQL or feature store) and ML-ready training / scoring datasets, through model registries, batch or real-time inference, and monitoring — with sound data-modelling practices and data-quality checks along the way. You know when to reach for gradient boosting, neural networks, linear models, or a blend.
• You have designed and analyzed A/B tests end-to-end — power calculations, choosing the right unit of randomization, guardrail metrics, interpreting inconclusive results.
• You have a proficient understanding of statistics — sample size, variance, multiple-comparisons, Bayesian reasoning.

Nice to Haves:

• You have hands-on experience with sequential and/or deep-learning recommender models — two-tower architectures, transformer-based rankers, or sequence embeddings.
• You have experience with uplift modeling and conditional average treatment effects for personalization.
• You are familiar with dbt, Snowflake, AWS (S3, SageMaker), Airflow, and Trino / data lake stacks.
• You have prior CRM / marketing / e-commerce ML experience — customer lifecycle segmentation, campaign attribution, contact strategy optimization.

What You'll Be Doing:

• You will design and maintain the data pipelines and ML-ready tables that power feature generation, model training, inference and impact measurement – with clear ownership of data quality, reproducibility and training-serving consistency.
• You will help the CRM tribe find the biggest opportunities for growth and personalization across the customer lifecycle — onboarding, engagement, activation, retention.
• You will own predictive/uplift or recommendation models that decide what to recommend and who to talk to, powering personalized CRM journeys end-to-end.
• You will model customer behavior, product-usage patterns and CRM engagement (email/push clicks) to identify who's likely to churn, who's ready for their next product, and measure how much value a campaign actually created.
• You will partner closely with Data Analysts, Data Engineers and CRM Campaign Managers, translating models into levers they can use.

Perks and Benefits:

• Flexible working - whether it’s working from home, school plays or life admin we get that flexibility is essential and you’re trusted to do the right thing and be responsible
• Stock options in a profitable company
• Relocation support
• Generous parental leave
• Pension scheme
• Paid sabbatical
• Loads of development opportunities
• Sports and wellbeing compensation
• A fun work environment with social activities and events
• The opportunity to work with super smart, curious people