Insights & Analytics Lead - North America

AXIS • Princeton, NY

21h • Hybrid

About The Position

The Insights & Analytics Lead – North America is a hands-on technical leader who turns business questions into high-quality insights, analytical solutions, and clear recommendations for North American underwriting teams. The role translates business requirements into data, analytics, data science, and AI requirements; explores complex data; identifies trends and opportunities; selects appropriate analytical approaches; and communicates conclusions to support informed decisions.

Working in an agile delivery model, the Lead partners with underwriting and other business stakeholders, Data Engineers, Data Scientists, AI Engineers, Architects, Technology experts, and business product owners to design, test, and deliver practical, scalable solutions aligned with measurable business outcomes. The role provides day-to-day technical leadership while remaining involved in analysis, solution design, and development of analytical outputs. It reports to the Insights & Analytics Director – North America.

The Lead identifies where analytics, machine learning, generative AI, agentic capabilities, or workflow automation can improve underwriting effectiveness, portfolio management, operational efficiency, or customer outcomes. They shape use cases and solution concepts, rapidly prototype to test feasibility and value, and support model development, testing, validation, deployment, and monitoring. Solutions must be explainable, fit-for-purpose, and aligned with AXIS data, AI governance, security, and responsible AI requirements. The role also promotes reusable analytical assets and tracks outcomes to improve solutions after release.

Requirements

• At least 7 years of experience in analytics, business intelligence, data science, or AI roles, including substantial hands-on experience analysing complex data and delivering data-driven solutions.
• At least 3 years of experience in insurance or reinsurance, ideally partnering with underwriting, portfolio management, or specialty insurance functions.
• Demonstrated ability to translate ambiguous business problems into structured analytical, data science, or AI requirements and deliverables.
• Experience delivering analysis or analytical products from discovery and data exploration through recommendation, implementation, and adoption.
• Experience working on cross-functional agile delivery teams with data engineering, AI engineering, data science, architecture, and technology colleagues.
• Experience communicating complex analysis and technical concepts to non-technical stakeholders through visualisations, written conclusions, and presentations.
• Strong practical SQL skills and proficiency in at least one analytical programming language, such as Python or R.
• Good understanding of data science and machine learning methods, model evaluation, and the lifecycle for bringing analytical solutions into production.
• Strong problem-solving ability combining technical depth, commercial judgement, and focus on practical business outcomes.
• Clear and credible communication skills, including adapting complex findings for technical and business audiences.
• Collaborative, delivery-focused approach and ability to work across business, Data & Analytics, and Technology teams.
• Comfort working iteratively, managing ambiguity, and balancing pace with quality, control, and maintainability.
• A degree or advanced degree in a relevant field, such as Data Science, Statistics, Mathematics, Economics, Business Analytics, Computer Science, or a related discipline, or equivalent professional experience.
• Ability to be in the office 3 days per week.

Nice To Haves

• Experience in North American specialty or commercial insurance underwriting analytics.
• Experience developing or deploying AI, machine learning, or advanced analytical solutions into production in an underwriting or portfolio management context.
• Experience with cloud data and AI platforms and modern development practices, such as version control, testing, and reusable code.

Responsibilities

• Partner with North American underwriting and business teams to understand objectives, decision points, pain points, and opportunities.
• Translate business requirements into clear data, analytics, data science, and AI requirements, including hypotheses, data needs, methods, success measures, and acceptance criteria.
• Challenge and refine requests to ensure solutions address the underlying business problem and are proportionate to value and complexity.
• Recommend appropriate analytical approaches, including analysis, reporting, visualisation, predictive modelling, machine learning, generative AI, or workflow automation.
• Frame analytical questions, develop hypotheses, select methods, and validate findings.
• Turn analysis into practical recommendations and explain business implications, limitations, and required actions.
• Identify opportunities for advanced analytics, machine learning, generative AI, and agentic capabilities to improve business outcomes.
• Shape solution concepts and technical requirements, including use cases, user journeys, data needs, model or AI behaviour, controls, evaluation criteria, and expected business value.
• Rapidly prototype analytical and AI-enabled solutions to test feasibility and value.
• Work with Data Scientists and AI Engineers on model development, testing, validation, deployment, and ongoing performance monitoring.
• Ensure solutions are explainable, fit-for-purpose, and compliant with AXIS data, AI governance, security, and responsible AI requirements.
• Contribute to cross-functional agile delivery, including technical analysis, solution design, backlog refinement, estimation, sprint planning, demonstrations, testing, and retrospectives.
• Promote reuse of data products, analytical methods, models, and components across the Insights & Analytics community.
• Define and track outcome-focused success measures and use feedback and performance evidence to improve released solutions.
• Explain analytical and AI concepts in clear business language and build confidence in the appropriate use of data-driven insights.

Benefits

• Competitive target incentive compensation, with awards based on overall corporate and individual performance.
• Comprehensive and competitive benefits package, including medical plans for the employee and family.
• Health and wellness programs.
• Retirement plans.
• Tuition reimbursement.
• Paid vacation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior