Top Tech Jobs & Startup Jobs in London

Develop and maintain scalable algorithmic insurance pricing models that combine actuarial science, machine learning, and specialty underwriting expertise. Responsibilities include model calibration, monitoring pricing metrics, exploring datasets and modeling approaches, supporting validation and stress testing, ensuring regulatory and commercial compliance, and contributing to the product roadmap. The role collaborates with underwriting, product, engineering, and data science teams while mentoring colleagues and communicating actuarial concepts across the business.

The FP&A Manager will lead financial planning, forecasting, management reporting, capital efficiency analysis, dashboards, ROI evaluations, and continuous process improvement. The role partners with Finance, Underwriting, Actuarial, Capital Modelling, Reinsurance, Technology, and senior executives to support strategic decisions, improve financial insight, and optimize capital allocation across the insurance business.

Analyze and improve actuarial data quality, reliability, governance, and reporting across Pricing, Reserving, and Portfolio Management. Investigate data issues, bugs, and business impacts; support pricing and portfolio reviews; identify data gaps; and provide actionable insights for commercial decisions. The role requires translating complex findings for technical and non-technical stakeholders while partnering with data teams and actuarial functions to improve analytical processes and digital underwriting capabilities.

Lead the design, development, optimization, and production deployment of machine learning and statistical models for automated insurance risk assessment and underwriting. Architect scalable data pipelines and infrastructure, collaborate with data scientists, engineers, and underwriters, mentor engineers, establish technical best practices, and evaluate emerging AI and machine learning techniques.

Leads the algorithm engineering team and partners with leadership to shape Ki’s underwriting algorithm strategy, architecture, roadmap, governance, and engineering culture. The role manages and develops high-performing engineers, guides machine learning product development, advises executives on technology strategy, supports regulatory compliance, and improves the organization’s digital underwriting capabilities.

Develop and evolve Ki’s end-to-end MLOps platform, including feature stores, model registries, monitoring, governance, and lifecycle management. Enable safe production deployment of machine learning, actuarial, and rules-based models. Own roadmap development, cost and vendor decisions, regulatory alignment, stakeholder adoption, and knowledge sharing. Coach early-career engineers and drive operational improvements across the digital underwriting capability.

Provides first- and second-line technical support for approximately 450 office and remote colleagues. Resolves Windows, macOS, Microsoft 365, access, networking, AV, and business application issues; manages devices through Intune and Autopilot; supports joiner, mover, and leaver processes; maintains assets, compliance, documentation, and service records; and contributes to automation, workplace technology projects, and continuous improvement.

The Senior Algorithm Engineer will develop machine learning-enabled products for underwriting, manage algorithm integrity, and enhance digital processes while mentoring junior team members.

Build, scale, and evolve Ki’s end-to-end MLOps system supporting underwriting, actuarial, rules-based, and machine learning models. The role improves production delivery speed and safety, promotes model management best practices, supports compliance, educates colleagues, identifies system enhancements, and mentors early-career team members. It requires collaboration across technical and commercial teams to advance digital underwriting capabilities.

Lead and grow engineering teams building a broker platform. Drive technical strategy, deliver microservice-based features, advocate Agile/Lean practices, recruit talent, measure team impact, and collaborate with senior stakeholders and CTO on architecture and infrastructure.