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# Senior Data Scientist

- **Company:** Women in Data
- **Location:** Greater London, UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Linux System Administration, Machine Learning, Software Construction, Google Cloud, Model Validation, Git, Software Version Control, Databricks
- **Published:** September 10, 2026
- **Apply:** https://www.collegerecruiter.com/job/2840591091-senior-data-scientist

## About the Role

You're a hands-on data scientist who enjoys solving real problems with data, and you communicate your thinking with clarity and confidence. You're collaborative, open, and comfortable operating in fast-paced, cross-functional environments., * Data science experience in commercial insurance.

 * Experience delivering advanced analytics or ML solutions that achieve sustained business impact.
 * Experience leading analytical workstreams or projects and coordinating inputs across multiple stakeholders.
 * Proficiency working in cloud-based Linux environments (e.g., Azure, AWS, GCP, Databricks).
 * Understanding of software engineering best practices, including git, modular code design, and reproducible workflows.
 * Excellent communication, storytelling, and stakeholder-management skills; comfortable presenting to senior, technical, and non-technical audiences.
 * Experience mentoring or coaching junior colleagues to raise the bar for the team.

## Description

As a Senior Data Scientist, you'll play a key role in a high-impact pricing and data science team within a leading commercial insurer. You'll bring solid technical expertise, deep commercial awareness, and the ability to lead analytical work that drives decision-making across the insurance value chain.

You'll act as a point of referral for the wider team, mentor junior data scientists, and help shape best practices in model development, governance, and responsible AI. This is ideal for someone ready to step into broader ownership, increased autonomy, and higher levels of cross-functional influence., * Lead multi-stakeholder analytical projects across underwriting, claims, operations, and customer functions; set structure, cadence, and deliverables.

 * Act as a technical point of referral for Data Scientists advising on modelling approaches, data quality, coding standards, and solution design.
 * Demonstrate specialist knowledge (e.g., pricing or domain-specific modelling) and apply it to complex business problems.
 * Present clear, compelling, and well-structured analyses to technical and non-technical audiences, with a sharp focus on commercial implications.
 * Translate ambiguous business questions into structured analytical problems; define success metrics and validation plans.
 * Ensure models and outputs meet governance, documentation, and regulatory standards (e.g., GDPR, EU AI Act); promote robust workflows, version control, testing, peer review, and model risk governance.
 * Contribute to evolving data science methodologies, internal tooling and governance frameworks.


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