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# Head of Data Science

- **Company:** Harnham
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £120,000.0 - £140,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Cloud Engineering, Python (Programming Language), Machine Learning, Standard Sql, SQL Databases, Large Language Models, Agentic-AI, Information Technology, Data Management
- **Published:** October 29, 2026
- **Apply:** https://www.reed.co.uk/jobs/head-of-data-science/57502808

## About the Role

The successful Head of Data Science must have the following skills and experience:

 * Proven experience building and deploying machine learning models in commercial environments.
 * Strong Python and SQL skills with experience working across modern cloud-based data platforms.
 * Practical experience with AI agents, LLM applications or agentic workflows.
 * Background within consumer-focused businesses where recommendation, decisioning or personalisation models have been applied.
 * Experience operating in fast-paced, evolving environments with a hands-on approach to delivery.
 * Strong academic background in a STEM subject such as Computer Science, Engineering, Mathematics or a related discipline., * Communication Skills (Key)
 * Data Analysis (Administration)
 * Data Science (Master)
 * Leadership and Management (Certhe)
 * Machine Learning
 * Python Programming (Beginner)
 * SQL Databases
 * Stakeholder Management (Business)
 * Statistical Knowledge
 * Team Management

## Description

This is a highly impactful individual contributor role with strategic responsibility for the direction of data science. You will own the development of predictive models, AI solutions and decisioning capabilities that directly influence customer outcomes and commercial performance.

Specifically, you can expect to be involved in:

 * Developing and enhancing predictive machine learning models for decisioning, risk and recommendation use cases.
 * Building and deploying AI and agent-based solutions into production environments.
 * Designing data science strategies that balance customer experience, operational efficiency and commercial objectives.
 * Working closely with product, engineering and business stakeholders to deliver measurable impact.
 * Driving experimentation, monitoring model performance and identifying new opportunities for advanced analytics.