Data Scientist

Job Type:

• →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. 

• 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