Senior Geospatial Data Scientist

Overview

Job Title: Senior Geospatial Data Scientist

Location: Bexhill/Leicester

Welcome to Hastings Direct

We’re a digital insurance provider with ambitious plans to become the best and biggest in the UK market. We’ve made huge investments in our pricing and data capabilities over the past few years, along with nurturing our 4

Cs culture.

We provide insurance for over four million customers, and we’re continuously seeking new ideas and diverse perspectives to challenge established thinking and drive meaningful change. Great pricing is built on trust, innovation and precision, so our aim is to ensure customers receive a fair and accurate price based on their individual risk, supporting fair outcomes while delivering sustainable and profitable growth for our company.

Pricing is more than just a number – it’s a strategic capability. At the heart of Hastings is deep risk insight – continually improving how we assess, segment and price risk through data and analytics.

The Role: The Senior Geospatial Data Scientist will oversee projects and modelling exercises which deliver cutting-edge data assets and predictive models that feed into Hastings’ market-leading pricing activities. This role sits within a combined team of Actuaries and Data Scientists, championing the adoption of the latest machine learning (ML) techniques to leverage powerful insights from vast amounts of customer information and data enrichment.

The Senior Geospatial Data Scientist will use their understanding of geospatial analytics and data science techniques to solve insurance problems and engineer powerful geospatial risk indices. We are looking to leverage advanced geospatial ML techniques to maximise commercial value, while ensuring a fair outcome for customers. The role requires mentoring junior data science colleagues and there is scope to manage a small team.

The role would suit a Geospatial Data Scientist with a track record of delivering powerful geospatial features and spatial machine learning models. Insurance experience is a bonus but not a requirement.

Your remit will include the following:

• Taking the technical lead in geospatial machine learning projects

• Develop best in-class models to predict features of a property or insured location

• Engineer powerful new geospatial rating factors to be deployed into our rating algorithms, understanding their impact and value

• Identify, analyse and monetise new data sources

• Manage and mentor more junior members of the Geospatial Data Science and Home Pricing teams

• Manage and maintain data and model updates

• Support the Geospatial team in the delivery of the team’s strategic objectives

Essential

• Experience engineering geospatial features and building predictive models

• Experience in the creation and development of models in Python, using the main Data Science libraries

• Keen interest in emerging ML techniques and the opportunities that these present in geospatial/insurance

• Experience planning and completing a project independently

• Strong Structured Query Language (SQL) coding skills and being comfortable with data manipulation

• Stakeholder management and communication skills with the ability to present technical ideas to a non-technical audience

Desirable

• Experience working with remote sensing datasets

• Image processing and segmentation experience

• Experience in a Personal Lines pricing team (motor or home)

• Experience with using Git Hub for version control and as a code collaboration tool

• Eagerness to work cross-functionally with Data Engineers, Data Scientists, Actuaries and Risk Pricing Analysts

• Natural problem solver who loves building quality solutions to complex real-world challenges

• Focuses on the bigger picture but not afraid to get into the detail when necessary

• Dynamic, flexible and delivery-focussed work ethic required to adapt to a fast paced working environment

• Takes ownership and accountability for their aspects of projects and work streams

Recruiter screening call

1st Round – Intro call with Hiring manager

2nd Round – Case study round

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