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# Head of Data Science

- **Company:** Formula.
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £130,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Transformation, Distributed Systems, Apache Hive, Python (Programming Language), Tensorflow, Azure Machine Learning, SQL Databases, Azure Data Factory, Pytorch, Snowflake, Scikit Learn, Operational Systems, Azure Synapse Analytics, Databricks
- **Published:** May 17, 2026
- **Apply:** https://find.jobs/jobs-near-me/head-of-data-science-london/2774739287-2/

## About the Role

* Proven experience leading a data science or advanced analytics function.
 * Deep technical expertise in Python, SQL and Spark SQL.
 * Hands-on experience with machine learning frameworks including TensorFlow, PyTorch and scikit-learn.
 * Experience with distributed computing and cloud platforms such as AWS, Azure Synapse or Snowflake.
 * Familiarity with data transformation tools (Databricks, Azure Data Factory) and ML platforms (Azure ML).
 * Strong commercial acumen with the ability to translate business problems into scalable, impactful solutions.
 * A track record of influencing at senior and executive level, with excellent stakeholder management skills.
 * Knowledge of governance, compliance and ethical AI frameworks.

## Description

* Lead, mentor and grow a team of data scientists, fostering a culture of innovation, rigour and continuous improvement.
 * Define and own the data science strategy, roadmap and ways of working across the function.
 * Take ownership of high-impact use cases spanning marketing, pricing, de\mand forecasting and AI innovation.
 * Design and oversee the delivery of predictive models and advanced analytics solutions that unlock new revenue opportunities.
 * Partner with senior leadership across Growth, Strategy and Technology to embed scalable data science solutions into operational systems.
 * Translate complex technical outputs into clear, compelling narratives for board-level and executive stakeholders.
 * Champion AI and machine learning innovation, staying ahead of industry best practice and emerging technologies.
 * Promote ethical data use, governance and compliance across all analytics initiatives.


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