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Senior data scientist (behavioural)

London
Harnham Search & Selection
Data scientist
Posted: 1 April
Offer description

Do you want to build predictive models that explain real-world patient behaviour at population scale?

Have you worked with Python and Databricks to develop and optimise production ML systems?

Are you ready to join a fast-moving AI team where you can shape a core data product?


About the company

We’re partnering with a fast-growing, London-based behavioural healthcare AI company building large-scale data products to understand what drives patient behaviour. Their core platform combines behavioural science and machine learning to deliver insights used by pharmaceutical organisations across clinical trials and commercial strategy.

The team is ~40 globally, operating in a highly collaborative, startup environment with strong technical leadership and real-world impact.


The role

They’re hiring a Senior Data Scientist to work on their flagship product, focused on predicting patient behaviour at scale. You’ll play a key role in developing and optimising machine learning models, integrating new datasets, and ensuring models are robust, explainable, and production-ready.


This is a hands-on role with real ownership, working closely with engineers, behavioural scientists, and product teams.


Key responsibilities

* Build and optimise predictive ML models using Python and Databricks
* Lead development of scalable modelling pipelines and data workflows
* Integrate new data sources (including behavioural and geospatial data)
* Validate models for performance, fairness, and real-world applicability
* Collaborate with product and engineering teams to deliver production-ready solutions
* Contribute to LLM-assisted development workflows


Key details

* Salary: £80k–£95k base
* Bonus: ~10%
* Equity: ISOs included
* Working model: Hybrid (2 days/week in Holborn – Mon & Thu)
* Tech stack: Python, Databricks, ML pipelines, LLM-assisted coding
* Visa sponsorship: Not available


Interested? Please apply below.

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