Hiscox Underwriting Group Services Ltd (HUGS)

Hiscox Underwriting Group Services Ltd (HUGS) is seeking a Tech Transformation Programme Manager based in London or York to lead significant technology-enabled initiatives within a multi-year change initiative. You will report directly to the CTO - Transformation, responsible for overall programme leadership, budget management, and building effective teams. The ideal candidate will have extensive experience in delivering large-scale technology transformations, specifically with MS Dynamics 365 and Power Platform. This role presents an exciting opportunity to drive innovation within a customer-focused organization.

Job Type: Permanent Location: London or York The organisation is currently undergoing a significant transformation as a core pillar of the Hiscox 2030 strategy, designed to make the organisation scalable, efficient, and increasingly customer-focused by modernising operations and embedding a "One Hiscox" mindset. It underpins the broader growth ambitions and is delivered through multiple strategic initiatives. The Technology Transformation enables 70% of these initiatives and contributes over half of the programme's projected benefits. The Tech Transformation Programme Manager will report directly to the CTO - Transformation and hold end-to-end accountability for leading and delivering the technology-enabled initiatives within the CRM & Telephony and Document Management delivery pillar within a multi-year, business-wide change initiative. Key Responsibilities Provide overall programme leadership, setting direction, priorities and managing resources across all stages of the technology transformation lifecycle. Engage, influence and collaborate with executive committee members and senior stakeholders to secure buy-in and alignment with the technology transformation delivery objectives and approach. Drive innovation and technical excellence across the programme ensuring solutions are robust and future-ready. Manage the delivery pillar budget of $15m+, monitor financial performance and ensure commercial value is delivered throughout the programme. Champion a culture of delivery excellence, ensuring milestones, quality standards and desired outcomes are consistently achieved. Build and lead an effective delivery team made up of technical specialists and delivery professionals, based on the needs of the programme. Identify risks and proactively manage issues, adapting plans as needed to maintain momentum and minimise disruption. Foster a collaborative, inclusive environment, supporting continuous improvement and the development of team members. Represent the organisation externally as a trusted ambassador for technology transformation. Candidate Profile Proven experience in delivering large-scale, complex technology transformation programmes implementing centralised CRM platforms (MS Dynamics 365 and Power Platform) that standardise data models and capture for distribution including customer and brokers; and implementing enterprise-wide archiving and document management solutions. 10 years or more in Project / Programme Management (less years but the right level of knowledge will naturally be considered). MS Dynamics and Power Platform is highly desirable. Insurance / Financial Services or other regulated industry experience is highly desirable. Outstanding stakeholder management and influencing skills, comfortable operating at all levels and with all stakeholders. Strong commercial acumen and demonstrable financial management experience, with a relentless focus on outcomes and quality. Resilient, adaptable, and forward-thinking, with a passion for innovation and future-focused solutions. Personal commitment to inclusivity, continuous learning and the development of others.

Overview Job Type: Fixed Term Position: Finance Business Systems Analyst Reporting to: Head of Finance Business Applications Location: London / York Band: II Type: 12 Month FTC (Maternity Cover) Do you thrive in a fast-paced environment and enjoy solving problems? We are looking for a Finance Business Systems Analyst that has strong Oracle Cloud EPM Solutions knowledge. You will focus on driving positive change, contribute to our growth, and shape the future of our Finance organisation and form close working relationships internally with Finance IT, the wider Finance team and business units. Key Responsibilities Support the EPBCS-based Forecast, Budget, and Long Range Plan Processes from a systems perspective Support the FCCS group consolidation process Support working day/planning timetable processes Support monthly /ad-hoc finance systems processes such as month end close, reconciliation, master data management, change requests etc Maintain and monitor change/ticket requests Create, maintain and monitor analysis of system performance, hierarchies and current processes with a focus on improving end-user experience Establish best practices and support user community training on Oracle Report development and Smartview Support the management of Oracle tools in the Finance function; including updates, UAT, process improvement, documentation, standard report development and chart of account maintenance Gather requirements from users and detail both process and technical requirements to translate end-user requirements into finished and working Oracle Applications Design, develop and enhance performance, processes and controls across all finance business applications Deliver high-quality change aligned to the finance business applications roadmap Create, maintain and manage documentation for all Oracle support initiatives and change requests Act as the bridge between understanding business needs and generating system requirements Support Finance in delivering continuous improvement using industry trends and best practices in finance system applications and automation toolsets Contribute SME knowledge to wider Hiscox change initiatives Qualifications Strong functional knowledge of Oracle Cloud Solutions and associated applications - preferred experience with EPBCS, PCMCS, FCCS, TRCS, and ARCS Experience working in or with a Finance function Experience with PowerBI suite to provide analysis and produce reporting across large data sets Solid understanding of financial processes and accounting principles Strong communication skills Excellent analytical and problem-solving skills Strong control mindset and experience Ability to prioritize and manage multiple tasks Reporting Relationships / Interactions Reports to the Head of Finance Business Applications. Maintains constructive and supportive professional relationships with internal and external stakeholders, including the Finance business unit, IT teams, internal project teams and external consultants. Diversity & Benefits At Hiscox we care about our people. We hire the best people for the job and are committed to diversity and creating a truly inclusive culture, which we believe drives success. Working life does not always have to be in the office; we have introduced hybrid working to encourage a healthy work-life balance. Our benefits package includes a bonus, contributory pension, 25 days annual leave plus 2 Hiscox days and a 4 week paid sabbatical with every 5 years' worth of service, private medical for all the family and much more.

Role Purpose As a Lead Machine Learning Engineer (MLE) at Hiscox, you will shape and scale our Machine Learning Engineering capability and ensure the successful deployment and operation of ML in production. You will lead the MLE sub chapter, line manage Machine Learning Engineers, and partner closely with the Head of Data Science, the Data Science sub chapters and Platform/Group teams to enable scalable, reusable, and well governed ML solutions. You will be accountable for the MLOps platform, ensuring it is reliable, secure, and continuously evolved and for ensuring our business unit ships ML to production in a scalable way that is reusable across value streams, enabling efficient model maintenance, monitoring, and lifecycle management. Combining deep technical expertise with leadership, you will set standards, uplift capability, and enable squads to deliver robust, production grade ML systems. Responsibilities People Leadership: Manage and grow talent; set objectives, conduct performance reviews, and guide career progression for the MLE sub chapter. Foster a strong engineering culture: Promote collaboration, psychological safety, and high standards of quality and reliability. Provide coaching and mentorship: Support technical and professional development of Machine Learning Engineers. Strategic Capability Development: Define and evolve chapter strategy; align sub chapter goals with chapter and organisational objectives. Shape technical direction: Establish standards for ML engineering, deployment patterns, and MLOps. Drive upskilling and cross skilling: Build capability in production ML, platform usage, and software engineering best practices. Technical Enablement & Platform Ownership: Own and evolve the MLOps platform; ensure it is reliable, secure, and scalable. Enable scalable and reusable ML delivery: Ensure ML solutions for the business unit are deployable across value streams and efficient to operate. Lead technical spikes and proof of concepts: De risk architectural decisions and explore new tools and approaches. Governance & Standards: Ensure compliance, security, architecture, and operational standards. Define guardrails for production ML systems covering deployment, monitoring, retraining, and decommissioning in collaboration with Data Science. Collaboration & Influence: Partner closely with the Data Science sub chapters and delivery team to ensure effective handover from experimentation to production. Represent Machine Learning Engineering in strategic forums and advocate for platforms, tooling, and scalable ML practices. Qualifications Bachelor's or Master's in Computer Science, Engineering, or a related quantitative field (or equivalent experience). Experience as a Senior/Lead Machine Learning Engineer delivering production ML systems at scale. Solid understanding of core data science concepts, including supervised and unsupervised learning, feature engineering, and model evaluation. Working knowledge of statistical concepts and model evaluation techniques sufficient to review, validate, and productionise data science work. Proven line management and/or technical mentorship of engineers; building capability and setting standards. Demonstrated ownership of MLOps platforms or critical ML services, including CI/CD, model serving, monitoring, and incident management. Proven ability to design, implement, and operate technical frameworks for evaluating the commercial impact of machine learning systems in production. Effective collaboration with Data Scientists across the end to end ML lifecycle. Experience working in Agile, cross functional squads. Insurance or financial services experience is a plus but not essential. Technical Skills Strong Python in a machine learning engineering context, with solid software engineering fundamentals (OOP, testing, design patterns). Production ML systems: Experience deploying, monitoring, and maintaining ML models in live environments. Cloud & infrastructure: Hands on experience with a major cloud platform (GCP, AWS, or Azure), including containerised deployments. MLOps & CI/CD: Experience with CI/CD pipelines, Git based workflows, and Infrastructure as Code (e.g. Terraform). Operational excellence: Understanding of API operations, monitoring, logging, and reliability considerations for ML services. Data & integration: Working knowledge of SQL and integrating ML services into wider data and application ecosystems. Why Join Us? This is an opportunity to shape the future of machine learning engineering at Hiscox, build a high performing sub chapter, and influence strategic decisions, while staying close to the craft you love. You'll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward thinking environment.

Job Type: Permanent Reporting to: RE&ILS Head of Data Location: London 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 for 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. Key Responsibilities 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. 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. 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. 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. 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. 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. 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 & Structure Reporting to: RE&ILS Head of Data; dotted line to Group Head of Data Science. 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. Key Experience Deep Interest in Leadership: Demonstrated mentoring and coaching of junior team members, with evidence of successful business outcomes driven using advanced Data Science/AI. Technical Depth: Extensive hands on experience in architecting, designing, and building complex ML models, with strong cloud services knowledge and AI/ML/LLM ecosystem understanding. ML Ops Maturity: Proven ability to build, maintain, and support production deployed models, establishing effective monitoring, evaluation, and refresh processes. AI and Data Governance: Mature understanding of AI and data governance, data obfuscation & privacy laws, data version control, lineage, and application of AI governance frameworks in a regulated environment. Stakeholder Management: Experience managing collaboration with business unit leaders and external technology partners. Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent. Technical Proficiency: Exceptional proficiency in Python (and R), SQL capabilities, mastery of machine learning & statistical modelling techniques, including generative AI, LLMs, AI Agents, NLP, CV.

Hiscox Underwriting Group Services Ltd (HUGS) is looking for a PMO Analyst to support governance and reporting across the UK change portfolio. The role involves maintaining governance standards, ensuring accurate data, and engaging stakeholders. The ideal candidate will have experience within a Portfolio Management Office and strong skills in stakeholder engagement and data management. This is a hybrid position, promoting a healthy work-life balance with 2 to 3 office days per week.

Job Type: Permanent About the role: We are seeking a PMO Analyst to support governance, reporting, and delivery oversight across the UK change portfolio. Working within a Portfolio Management Office (PMO), you will help ensure strong governance, accurate portfolio data, and consistent reporting across a wide range of initiatives. You'll work closely with delivery leads and stakeholders to maintain governance standards, meet reporting cycles, and ensure key data (e.g. risks, issues, dependencies, financials) is accurate and up to date. This is a hands on role in an evolving environment where you'll be expected to proactively engage stakeholders, manage competing priorities, and support continuous improvement of PMO processes, tools and ways of working, including the use of data and automation tools such as Power BI. Key Responsibilities Portfolio Governance - Work with the PMO Manager and Portfolio Office Lead to ensure effective management of the portfolio through appropriate and robust governance and controls. Own and maintain governance collateral such as Terms of Reference, meeting inputs and outputs. Own and manage the Lessons Learned process, working with stakeholders to embed lessons in portfolio collateral, processes and ways of working. Own and maintain relevant SOPs for owned PMO processes. Work with portfolio stakeholders to implement, own and maintain portfolio health assessment processes. Contribute to, and maintain, the Change Delivery Framework, governance processes and tools. Assist Project Managers in following frameworks and best practices, working to agree pragmatic solutions and escalating, if necessary. Support the deployment and application of the Change Delivery Framework and provide guidance to stakeholders. Support continuous improvement of PMO processes, tools and templates, proactively identifying areas for improvement and leading identified improvements. Work with relevant delivery leads to identify, manage and track risks, issues, assumptions and dependencies across the UK Portfolio. Data Accuracy & Reporting - Use appropriate data tools (e.g. Power BI, Power Automate) to present data, ensuring portfolio can make data led decisions in governance forums and that data sources are accurate, up to date and aligned. Create, analyse and distribute Management Information, including RAID data, to key stakeholders in a timely manner. Identify opportunities for data quality improvements, working with the PMO Manager to agree improvement plans with stakeholders. Ensure information reflects the true position of initiatives and projects; produce accurate reports for regular and ad hoc meetings and overall governance. Ensure all relevant information is accurate and remains up to date on portfolio management tools across all initiatives, aligning with master data sources and working with data owners. Monitor data accuracy and completeness, proactively chasing updates from stakeholders and data owners. Work closely with Project delivery leads to ensure reporting deadlines are met and reports are clear, consistent and of high quality. Stakeholder Engagement - Build strong relationships with project, product and programme teams and effectively engage stakeholders to ensure effective delivery of the portfolio. Qualifications Proven experience working as a PMO Analyst within a Portfolio Management Office supporting complex change portfolios, within the insurance or financial services sector. Strong experience of portfolio level governance and control processes, including working across multiple concurrent initiatives and stakeholders. Demonstrable experience working in fast paced or evolving environments, ideally where PMO processes and maturity are being developed or improved. Strong understanding of project and change delivery lifecycles (e.g. Agile, Waterfall, or hybrid approaches), with experience supporting delivery rather than leading projects. Excellent stakeholder management skills, with the confidence to proactively engage, chase updates, and manage competing priorities across multiple teams. Strong attention to detail, with a proven ability to maintain high data accuracy and integrity across portfolio reporting. Experience working with portfolio data, reporting, and management information, including risks, issues, dependencies, financials and benefits tracking. Strong analytical capability, with experience using tools such as Excel (advanced), Power BI and Power Automate (or similar). Ability to work independently and manage workload across multiple governance cycles and deadlines. Clear and effective communication skills, with the ability to work with stakeholders at all levels. Nice to Have Relevant PMO and/or project management qualifications such as P3O, MoR, MoP. Experience of working in the insurance industry. Flexible Working We operate a hybrid way of working to encourage a healthy work life balance, with 2 to 3 days in the office per week.

Hiscox Underwriting Group Services Ltd (HUGS) is seeking a Principal Data Scientist to lead complex data science initiatives and transform underwriting capabilities. You will mentor junior data scientists and collaborate with various business functions to maximize value across the insurance value chain. The ideal candidate will have a degree in a quantitative field and substantial experience in data science, particularly in machine learning and statistical modeling. A strong ability to communicate complex findings to diverse audiences is essential, alongside proficiency in Python and SQL.

Build a brilliant future with Hiscox. As a Principal Data Scientist you will be an integral part of a dynamic technical team, strategically focused on leveraging data science across our diverse business functions. Your expertise will transform underwriting capabilities and extend through the entire insurance value chain, championing a multi-disciplinary approach to complex problem solving. You will lead the end to end delivery of our most significant and complex data science initiatives, driving technical strategy, architecture, and best practices. You will mentor and coach junior and mid level colleagues, elevate the overall team capability, and collaborate extensively with other disciplines to maximise business value. Key Responsibilities Utilise industry standards, emerging methodologies and empirical research to develop critical business inputs and assist leaders in innovating their approaches. Technically lead the end to end delivery of our most complex data science initiatives, encompassing strong understanding of intricate business challenges and translation into technical problem statements, working with diverse datasets (internal and external), and expert application of advanced machine learning or statistical modelling techniques to generate actionable insights and measurable impact. Provide hands on technical mentorship and guidance to junior and mid level data scientists, fostering best practices, elevating technical standards and cultivating advanced skill development within the team. Engage closely with other members of the data and analytics community at Hiscox to deliver value through various analytics techniques, sharing advanced knowledge and driving the adoption of robust analytical capabilities. Design, implement and maintain robust technical frameworks for monitoring, evaluating and quantifying the commercial impact and efficiency of data science solutions, ensuring continuous value demonstration. Person Specification Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent. Extensive professional experience in data science, with a proven track record of technically leading and successfully delivering complex, impactful, and production grade data science solutions. Background in data science within finance or insurance advantageous but not required. Demonstrated capacity for independent, high quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill defined and challenging business problems. Proven ability to design, implement, and maintain robust technical frameworks for evaluating commercial impact. Proven ability to technically mentor data scientists, fostering best practices, elevating technical standards, and contributing to the overall technical growth of the team. Strong understanding and practical experience with Agile development methodologies and software engineering best practices (e.g., version control, comprehensive testing, modular code) relevant to data science product delivery. Ability to articulate complex technical findings and methodologies into clear, concise, and actionable insights for diverse audiences, effectively influencing technical and non technical stakeholders to drive data driven decision making and solution adoption. Demonstrable experience collaborating effectively with cross functional teams (e.g., engineering, product, business stakeholders) to translate business challenges into robust technical requirements and ensure seamless delivery. Key Technical Skills Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree based methods to advanced deep learning architectures. Practical experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs) and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions. Solid understanding of foundational statistics and experimental design. Familiarity with or experience on cloud platforms. Impact and Achievements Pioneer the development and robust deployment of highly impactful machine learning and AI driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization. Translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real world adoption and beneficial outcomes of our analytical work. Actively elevate the technical maturity and capabilities of the data science team by shaping and implementing industry leading AI, data, and analytics techniques, methodologies, and engineering best practices.