Lead Data Scientist

Lead Data Scientist page is loaded Lead Data Scientistremote type: Hybridlocations: Londontime type: Full timeposted on: Posted Todayjob requisition id: R Job Type: Permanent Build a brilliant future with Hiscox Reporting to: Re & ILS Head of Data Location: LondonType: Permanent Role Overview The Lead Data Scientist is a crucial member of the extended RE&ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New) Data Science and Machine Learning chapter.This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).You will co-lead the new Data Science chapter with the RE&ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&ILS strategic Value Streams. Whilst the chapter grows, you are expected to be hands-on actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the Group AI Governance Framework and maintains rigorous data governance standards. You will be accountable of this adherence.This is likely to be your first managerial role and the first time you have had one or more direct reports - having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders - Head of Data and the Hiscox Group Head of Data Science as well. About Hiscox Re & ILS Hiscox Re & ILS is located in Bermuda and London and underwrites reinsurance risks from around the world on behalf of our own and other people's capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision. Key Responsibilities 1. Chapter Leadership & Talent Management People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture. In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths. Culture & Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members. Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice. Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn - especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value. 2. Solution Delivery & ML Ops Excellence Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions. ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour. Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast - as a lot of AI use cases will be highly experimental in nature with no guarantees of success. Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models. 3. Strategy, Governance & Innovation Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains. Governance & Compliance: Champion data and model governance, working within the Group AI Governance Framework . Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work. Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&D to deliver reliable insights and potential next steps quickly. Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership. Required Experience and Structure Reporting: Reports into the RE&ILS Head of Data with a dotted line into the new Group Head of Data Science. Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&ILS Data Science Chapter. Key Partners: RE&ILS CTO, Group Head of Data Science, RE&ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft). Candidate Profile The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards.