Data Science Manager - ML / AI - Insurance

JR United Kingdom; London; Hybrid; GBP 80,000 - 130,000; Full time

Job summary

A leading Lloyd’s market insurer seeks a Data Science Manager to drive innovation in analytics. This role includes leading a team to enhance underwriting and pricing decisions through advanced data-driven solutions. Applicants should possess strong knowledge in data science, programming skills, and experience in the insurance sector.

Benefits

Up to 60% Bonus

Up to 17% Pension

Comprehensive Benefits Package

Qualifications

• Proven experience managing Data Science teams and delivering impactful analytics projects.
• Advanced knowledge in statistical modeling and machine learning techniques.
• Expert-level programming skills, particularly in Python.

Responsibilities

• Lead and manage a high-performing team of Data Scientists.
• Collaborate with stakeholders to design AI and machine learning solutions.
• Build and refine data-driven models to optimize risk appetites.

Skills

Data Science Management

Stakeholder Management

Statistical Modelling

Data Manipulation

Machine Learning

Programming in Python

Azure Cloud Technologies

Collaboration

Education

Relevant Quantitative Discipline

Tools

Azure Data Factory

SQL

Synapse Analytics

PowerBI

Job description

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Data Science Manager - ML / AI - Insurance, london

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Client:

Stott and May

Location:

london, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

2

Posted:

31.05.2025

Expiry Date:

15.07.2025

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Job Description:

Data Science Manager - ML / AI - Insurance

Location: London (Hybrid)

Employment Type: Permanent, Full-Time

Department: Data Science and Analytics

Up to 130K + Up to 60% Bonus + up to 17% Pension + Benefits

Overview

An innovative Lloyd’s market insurer is seeking a Data Science Manager to lead a growing team in building cutting-edge data-driven solutions that directly impact underwriting, pricing, and risk selection. This is an exciting opportunity to influence strategic decisions and drive digital transformation across the business.

The company has a strong reputation for top-quartile performance and a forward-thinking, collaborative culture. You’ll join a team that empowers its underwriters and invests in long-term, sustainable growth.

Key Responsibilities

As the Data Science Manager, you will:

• Lead and manage a high-performing team of Data Scientists, delivering projects that enhance risk ranking, digital trading, pricing, and profitability analytics.
• Collaborate with stakeholders across Underwriting, Technology, Actuarial, and Analytics to design and implement advanced machine learning and AI solutions.
• Build and refine data-driven models to optimize risk appetite alignment, loss classification, and technical rating methodologies.
• Contribute to digital trading initiatives by developing broker data insights and automation tools for the Digital-Follow channel.
• Define strategic data requirements and partner with Data Engineers to ensure efficient data pipelines and model deployment.
• Present findings to senior leadership and support the development of management and board-level reports.
• Champion best practices in data governance, model validation, and analytics delivery across the business.

What You’ll Bring

• Proven experience managing Data Science teams and delivering business-impactful analytics projects.
• Strong stakeholder management skills, with the ability to communicate complex technical ideas to non-technical audiences.
• Advanced knowledge of statistical modelling, data manipulation, and machine learning techniques.
• Expert-level programming skills, particularly in Python.
• Familiarity with Azure cloud technologies (Data Factory, SQL, Synapse Analytics, PowerBI) is a strong plus.
• Experience in Data Science or Actuarial roles, ideally within the insurance or Lloyd’s market.
• A collaborative mindset with the ability to work cross-functionally across analytics, actuarial, data engineering, and IT teams.
• Strong academic background in a relevant quantitative discipline.