Level

Hiscox

Data Scientist

AI in this role

prompt-engineering

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

How we rate this

Data Scientist at Hiscox rates 82 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt Engineering

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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