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
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
Experience defining solution governance frameworks — handoff documentation, acceptance criteria, deployment standards
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
Desirable
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.
