Analytics Solutions Lead

Chubb Ltd.

Greater London

Hybrid

GBP 110,000 - 160,000

Full time

2 days ago

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Benefits offered by this job

Salary and pension scheme

Discretionary bonus

Hybrid working options

Private Medical cover

Employee Share Purchase Plan

Life Assurance

Subsidised gym membership

Learning & development offerings

Employee Assistance program

Job summary

Chubb Ltd. in the United Kingdom seeks a senior Analytics Solution Lead to translate analytics and AI into production for our EMEA insurance business.

You will embed with underwriting, pricing and portfolio management to deploy production-grade analytics that drive measurable commercial outcomes. This delivery-focused role blends data science, engineering and business, ensuring deployment reliability, governance and responsible AI.

Qualifications

8+ years in data science, analytics, or forward-deployed analytics roles with production experience.
Experience deploying analytics end-to-end from problem framing to production and measurement.
Proven ability to engage with senior business stakeholders and drive adoption.

Responsibilities

Embed with business stakeholders to understand decision changes analytics can drive.
Deploy solutions rapidly and iteratively with field feedback.
Drive adoption: ensure tools and models are used, understood and trusted.

Skills

Analytics deployment

GenAI / LLM deployment

Python proficiency

Azure cloud

MLOps concepts

Stakeholder engagement

Production-grade analytics

Underwriter interactions

Tools

MLflow

Azure ML

Duck Creek / Guidewire / Acturis

Job description

This is a senior, forward‑deployed analytics leadership role — responsible for taking analytics and AI capabilities out of development and into the commercial reality of Chubb's EMEA insurance business.

This role is not a central analytics function. It is a deployment‑first role, embedded at the intersection of data science, engineering, and business — where the measure of success is analytics operating reliably in production, driving measurable commercial outcomes.

The Analytics Solution Lead owns the full journey from analytical development to business adoption: designing production‑ready solutions, driving deployment into operational systems, and embedding analytics into how underwriters, pricing teams, and portfolio managers actually make decisions. You will bring field learnings back to sharpen the analytics roadmap, proactively identify new deployment opportunities across the business, and lead the cultural shift that turns analytical output into operational capability.

It is a delivery and adoption role — combining the technical credibility to work alongside AI engineers, data scientists and architects, the business fluency to engage senior underwriting ,pricing and Ops leaders, and the deployment mindset to get things done in complex, regulated environments.

Core Responsibilities

Embed directly with business stakeholders — underwriters, pricing leads, portfolio managers — to understand how analytics can change how they make decisions, not just what information they have

Deploy solutions rapidly and iteratively: ship working capability quickly, gather real-world feedback, and improve — consistent with a field-first deployment philosophy

Drive adoption of deployed analytics: ensure tools and models are being used, understood, and trusted by the people they were built for

Define solution specifications and deployment requirements that enable Solution Architects and Deployment Engineers to build and release production-grade analytics solutions

Collaborate with Solution Architects to ensure analytics designs conform to enterprise architecture standards, platform constraints, and non-functional requirements (scalability, security, latency, auditability)

Define measurable success criteria for every deployed solution — not just technical metrics, but commercial outcomes (e.g. pricing accuracy, hit rate improvement, loss ratio movement, underwriter decision quality)

Design and lead change management plans for analytics deployment — ensuring that new tools and models are adopted, not just installed

Develop and deliver targeted enablement for business users: from underwriter training on model outputs to pricing team workflows that embed decision support

Qualifications

Required Experience

8+ years in data science, analytics, analytics engineering, or forward‑deployed analytics/AI roles — with a demonstrable track record of getting analytics into production in complex organisations

Proven experience deploying analytics solutions end-to-end — from problem framing through to production, adoption, and impact measurement

Experience embedding directly with business stakeholders and driving behavioral change through analytics — not just delivering technical outputs

Demonstrated ability to measure and communicate the commercial impact of analytics deployments

Experience working across analytics and engineering teams — translating model outputs and analytical designs into deployment-ready specifications

Ability to engage credibly with Solution Architects on design trade-offs, platform constraints, and integration patterns

Experience designing and operating model monitoring frameworks — drift detection, performance tracking, alerting

Exposure to GenAI / LLM deployment in enterprise settings

Cloud platform experience — Azure preferred

Experience working in regulated industries — insurance or financial services strongly preferred

Demonstrable experience with responsible AI practices — explainability, bias review, model auditability

Experience with insurance platforms (Duck Creek, Guidewire, Acturis)

Experience with pricing or actuarial model deployment

Familiarity with MLOps concepts (CI/CD pipelines, model registries, automated testing) — awareness required, not hands‑on ownership

Experience with ML lifecycle tooling — MLflow, Azure ML, or equivalent

Python proficiency — able to read and review analytical code, contribute where needed

Consulting or forward‑deployed engineering background (Palantir, QuantumBlack, or equivalent)

Experience leading or mentoring data scientists and analytics professionals

We offer in return!

Competitive salary & pension scheme, discretionary bonus scheme, 25 days annual leave plus ability to purchase 5 additional days, hybrid working options, Private Medical cover, Employee Share Purchase Plan, Life Assurance, Subsidised gym membership, Comprehensive Learning & development offerings, Employee Assistance program.

Integrity. client focus. respect. excellence. teamwork

Our core values dictate how we live and work. We’re an ethical and honest company that’s wholly committed to its clients. A business that’s engaged in mutual trust and respect for its employees and partners. A place where colleagues perform at the highest levels. And a working environment that’s collaborative and supportive.

Diversity & Inclusion. At Chubb, we consider our people our chief competitive advantage and as such we treat colleagues, candidates, clients, and business partners with equality, fairness and respect, regardless of their age, disability, race, religion or belief, gender, sexual orientation, marital status or family circumstances.

We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a disability or long‑term condition (for example dyslexia, anxiety, autism, a mobility condition or hearing loss) and need us to make any reasonable adjustments, changes or do anything differently during the recruitment process, please let us know.

Job Info