Asks for

The ad says“Working knowledge of generative AI techniques and technologies, including large language models (LLMs), prompt engineering techniques, AI-assisted coding tools, and agentic AI workflows.”
The ad says“Working knowledge of generative AI techniques and technologies, including large language models (LLMs), prompt engineering techniques, AI-assisted coding tools, and agentic AI workflows.”
The ad says“Willingness to learn and apply engineering best practices, including version control, testing, code review, and reproducible development workflows.”
The ad says“Experience using statistical analysis, machine learning, generativeAI, and data science techniques to identify trends, generate insights, and support business decision-making.”
The ad says“Working knowledge of generative AI techniques and technologies, including large language models (LLMs), prompt engineering techniques, AI-assisted coding tools, and agentic AI workflows.”
The ad says“Experience using statistical analysis, machine learning, generativeAI, and data science techniques to identify trends, generate insights, and support business decision-making.”
The ad says“Working knowledge of generative AI techniques and technologies, including large language models (LLMs), prompt engineering techniques, AI-assisted coding tools, and agentic AI workflows.”
The ad says“Experience with analytical tools, programming languages, and databases, such as Python and SQL.”
The ad says“Willingness to learn and apply engineering best practices, including version control, testing, code review, and reproducible development workflows.”
The ad says“Experience with analytical tools, programming languages, and databases, such as Python and SQL.”
The ad says“Experience using statistical analysis, machine learning, generativeAI, and data science techniques to identify trends, generate insights, and support business decision-making.”
The ad says“Willingness to learn and apply engineering best practices, including version control, testing, code review, and reproducible development workflows.”
The ad says“Willingness to learn and apply engineering best practices, including version control, testing, code review, and reproducible development workflows.”

Job Type:

Permanent

Build a brilliant future with Hiscox

As a Data Scientist at Hiscox, you will take on a high-impact role, acting as a critical thinker and problem solver for the business. You’ll apply your core technical skills and innovative thinking to tackle complex challenges, identify opportunities, and help shape data-driven decision-making across the London Market.

You’ll operate across a wide variety of business functions, managing multiple priorities and delivering both ad hoc analysis and predictive/prescriptive models. Your work will contribute directly to building Hiscox’s data culture and enabling evidence-based decisions in a fast-paced, evolving environment. Communicating the business value of your analytical solutions to stakeholders will be a key part of your role.

You’ll be part of an award-winning team, recognised for its pioneering collaboration with Google to deliver the market’s first AI-enhanced lead underwriting solution. This achievement reflects the team’s commitment to innovation, impact, and excellence in applying data science to real-world insurance challenges.

As a Data Scientist, you’ll work within a wider technical team whose efforts span multiple business functions, bringing a multi-disciplinary approach to problem solving and analysis.

This is an ideal role for someone who is passionate about using analytics to influence decisions and is keen to continue learning and delivering value through data. You’ll be expected to conceptualise new approaches, communicate your vision to stakeholders, and see ideas through to implementation.

Key Responsibilities:

Leveraging industry standards, emerging methodologies and empirical research to develop critical inputs to business information and helping business leaders develop innovative approaches to driving their business.

Working on the end-to-end data solution including understanding complex business challenges, designing solutions, working with large and small data sets (including 3rd party and internal data of a wide variety), using cutting-edge machine learning or Generative AI techniques

Work collaboratively with data scientists and other technical disciplines including product and business teams

Work closely with other members of the data and analytics community at Hiscox, contributing to delivering value though the use of a range of analytics techniques.

Person Specification:

Degree in a STEM or closely related field or equivalent experience. A further degree is a plus.

Practical data science experience, applying analytical techniques to solve business problems and deliver valuable insights. Experience of data science in finance or insurance is advantageous but not required.

Experience conducting data analysis, experimentation, and model development to address business challenges. Comfortable using generative AI technologies, including AI-assisted coding tools, to accelerate research, development, and problem-solving, while maintaining a thorough understanding of the methods, code, and outputs produced.
Able to critically review, validate, and take ownership of AI-assisted work, ensuring solutions are accurate, explainable, and fit for purpose, while working effectively both independently and as part of a team.

Skills:

Experience using statistical analysis, machine learning, generativeAI, and data science techniques to identify trends, generate insights, and support business decision-making.

Experience with analytical tools, programming languages, and databases, such as Python and SQL.

Working knowledge of generative AI techniques and technologies, including large language models (LLMs), prompt engineering techniques, AI-assisted coding tools, and agentic AI workflows.

Interest in a broad range of data science, machine learning, and AI techniques, with an eagerness to learn about emerging technologies and industry best practice.

A strong grounding in statistical concepts and their practical application.

Experience working both independently and collaboratively within small, cross-functional teams to deliver analytics and data science projects.

Strong verbal, written, and presentation skills, with the ability to communicate technical concepts and insights clearly to both technical and non-technical stakeholders.

Willingness to learn and apply engineering best practices, including version control, testing, code review, and reproducible development workflows.
Exposure to cloud platforms such as Google Cloud Platform (GCP) is advantageous but not essential.
Knowledge of the insurance industry is beneficial but not required.

Work with amazing people and be part of a unique culture

Asks for

Values