Principal Data Scientist in London

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.