AI Governance Lead

VIQU IT Recruitment
London, United Kingdom
2 weeks ago
£90,000 – £110,000 pa
Applications closed

Related Jobs

View all jobs

Data Architect

Experis Croydon, London, United Kingdom
£700 – £750 pd Hybrid Clearance Required

Data Governance Manager

TRIA London, United Kingdom
£62,000 – £72,000 pa Hybrid

Head of Data Architecture & Governance

Peabody Chaucer, London, United Kingdom
On-site

Data Governance Manager

Softcat Manchester, United Kingdom
Hybrid

Data Governance Manager

Softcat Birmingham, West Midlands (county), United Kingdom
Hybrid

Head of AI & Automation

Experis United Kingdom
£85,000 – £100,000 pa Permanent

Salary

£90,000 – £110,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
Hybrid
Seniority
Lead
Education
Degree
Posted
30 Apr 2026 (2 weeks ago)

Benefits

Bonus

AI Governance Lead
London - Hybrid
£90,000 - £110,000 + bonus

VIQU has partnered with a leading insurance organisation, undergoing significant data and AI transformation, as they continue to embed advanced analytics and AI capabilities across their business. They are now seeking a AI Governance Lead to join their Chief Data Office, responsible for establishing and embedding robust AI governance frameworks, ensuring the ethical and compliant use of AI, and enabling the organisation to scale AI adoption in a controlled and responsible way. This role will operate at the intersection of data science, risk, and regulation, working closely with senior stakeholders to drive innovation whilst managing risk in a highly regulated environment.

Key Responsibilities of the AI Governance Lead:

• Define and implement the organisation’s AI governance framework, aligned to business objectives and regulatory requirements.
• Establish policies and standards to ensure the responsible, ethical, and compliant use of AI across the organisation.
• Identify, assess, and mitigate AI-related risks, including bias, privacy, and model explainability.
• Develop governance models across key insurance use cases such as underwriting, pricing, claims, and fraud.
• Implement controls, monitoring, and audit processes for AI models and data usage.
• Ensure compliance with regulatory frameworks including GDPR, FCA guidelines, and emerging AI regulations.
• Monitor AI model performance, accuracy, and fairness, implementing continuous improvement processes.
• Develop reporting frameworks, dashboards, and governance metrics to provide visibility of AI risk and performance.
• Collaborate with data science, technology, and risk teams to embed governance into AI development and deployment lifecycles.
• Engage with senior stakeholders and executive leadership to communicate governance strategy, risks, and opportunities.

Essential Requirements of the AI Governance Lead:

• Proven experience leading AI or ML governance within insurance or financial services environments.
• Strong background in data science, machine learning, or AI, with hands-on experience earlier in career.
• Experience managing AI model development and deployment within regulated environments.
• Strong understanding of insurance processes such as underwriting, pricing, claims, or fraud.
• Knowledge of regulatory frameworks including GDPR, FCA, and AI governance standards.
• Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
• Ability to translate complex business challenges into AI-driven solutions.
• Strong stakeholder management skills, with experience operating at senior or executive level.
• Understanding of actuarial principles and insurance analytics is highly desirable.
• Relevant certifications in AI, machine learning, or data science would be advantageous.

To discuss this exciting opportunity in more detail, please APPLY NOW for a no obligation chat with your VIQU Consultant. Additionally, you can contact Katie Dark on .

If you know someone who would be ideal for this role, by way of showing our appreciation, VIQU is offering an introduction fee up to £1,000 once your referral has successfully started work with our client (terms apply).

AI Governance Lead
London - Hybrid
£90,000 - £110,000 + bonus

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data Science Jobs UK 2026: roles, salaries and the trends shaping UK data science hiring over the next three years — from MLE crossover to GenAI workflows. Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

New Data Science Employers to Watch in 2026: a UK and international shortlist of analytics and AI companies hiring data scientists, ML engineers and analysts. Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.