Data Scientist

Job Type:

Permanent

Build a brilliant future with Hiscox
 

Locations: London/York

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 clearly 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 scientific solutions, working with large and small data sets (including 3rd party and internal data of a wide variety), using cutting-edge machine learning or statistical modelling techniques to derive insights

Work collaboratively with data scientists, data engineers and other technical people including pricing and underwriting teams in order to help support maturation of analytics practice within the organisation.

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.

Experience of data science, advanced analytics or a genuine interest to learn.

Experience of data science in finance or insurance is an advantage but not required.

Ability to conduct high quality research in a suitably timely manner working in both independently and in small teams as required by the task.

Familiarity with version control, agile working and other IT delivery tools is required

Skills:

Experience in developing predictive and prescriptive analysis (predictive modelling, machine learning or data mining) used to draw key business insights and clearly articulate findings for target audience.

Experience with analytical tools / programming languages and databases (for example: Python, R, SQL).

Experience with large language models and prompting, GCP experience is a plus.

Interest in a variety of machine learning techniques from simple linear models and random forests to deep learning.

A particular interest in natural language processing or machine vision.

A strong grasp of foundational statistics is essential.

Experience working both in small teams and independently on analytics projects.

Strong verbal and written communications skills and effective presentation skills. This is absolutely essential since you will have a lot of exposure to different internal stakeholders.

Willingness to learn best practice in software development.

Knowledge of insurance is an advantage but not essential.

Apply now for further information

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