Data Scientist

Job Type:

Permanent

Build a brilliant future with Hiscox
 

Data Scientist – Must have Insurance experience

Reporting to the Group Claims Data & Insights Manager

London/York/Atlanta/Lisbon – Hybrid working

The role:

You'll be a technically excellent problem-solver responsible for providing in depth analysis across our diverse portfolio in addition to building and maintaining Machine Learning models on the Group Claims Data Platform. Insurance experience and understanding is essential as you'll be operating across various territories and business platforms which include commercial, retail and personal lines products.

Along side insurance knowledge, strong SQL and Python skills will be key to develop and industrialise statistical/analytical models to predict claims outcomes, solve business problems and help to influence our underwriting/reserving strategies.

You will be communicating with both Senior and Executive level stakeholders and taking ownership of complex problems whilst being the gate keeper of industry best practises. We are looking to tightly define abstract problems, so a strong mathematical/programming background is needed, but you must also be comfortable with ambiguity.

In this post you will be part of a global agile scrum delivery team and will be expected to work with the team to meet the sprint goals, which drive towards the data platform product vision.

Key responsibilities:

• Be a core member in the team delivering the Data Strategy, working in an agile methodology, to deliver trusted governed Data Science outcomes for the business.
• Work with a diverse group of data consumers across the Group to identify and capture business requirements, which can then be met with advanced analytics and machine learning solutions.
• Design and develop analytical models (primarily using Databricks’ MLflow) on the cloud data platform following best practices for end-to-end model lifecycle (e.g. exploratory data analysis, model development, model training, model deployment and retraining)
• Maintaining a continual feedback loop with claims, underwriters and actuaries on segmentation/trend analysis and portfolio monitoring and optimisation – Trilogy Forum Group.
• Own, maintain and follow development and design principles as well as best practice (e.g. testing, performance tuning, source control, peer review). Create and maintain analytical model related documentation (e.g. solution design documentation, feature engineering design, details on experiments)
• Manage and deliver ad-hoc analytics requests from business stakeholders.

In terms of skills and experience required for the position, the following are important:

• Knowledge of Insurance, very desirable is Claims knowledge.
• A deep understanding of data science, analytics platforms/ML domains, especially GenAI and NLP.
• Experience with frameworks (eg. PyTorch, TensorFlow, or JAX) and LLM’s (e.g. prompt engineering, fine tuning, RAG).
• Experience building and fine-tuning various ML Models (supervised and unsupervised models, classification, clustering, regression etc)
• Hands on experience with common ML libraries such as Hugging Face, XGBoost, PyTorch, TensorFlow)
• Track record of building and deploying ML models in production with ability to monitor and remediate model decay of production ML models.
• Can provide data driven executive insights and communicate effectively.
• SME knowledge of technology architectures & processes involved in the modelling of data
• Strong coding experience in Python, in a data science context and a good grounding in SQL. Any Databricks, MLFlow and Spark experience would be advantageous.
• Up-to-date knowledge of data privacy & security standards in an Insurance context
• Comfortable with manipulating and analysing large datasets including data cleansing to provide insight to the business.

Innovation

• Can suggest and implement innovative data solutions to meet user requirements, continuously research best practices to optimize existing processes and develop innovative data based solutions in the data science space (e.g. Generative AI)

• Can work in partnership with other technical areas of the business such as Actuaries, Underwriting Insights, Data Engineers, IT and Solutions Architecture to drive the use of modelling, automation and analytics.

About Hiscox

As an international specialist insurer we are far removed from the world of mass market insurance products. Instead we are selective and focus on our key areas of expertise and strength - all of which is underpinned by a culture that encourages us to challenge convention and always look for a better way of doing things.

We insure the unique and the interesting. And we search for the same when it comes to talented people. Hiscox is full of smart, reliable human beings that look out for customers and each other. We believe in doing the right thing, making good and rebuilding when things go wrong. Everyone is encouraged to think creatively, challenge the status quo and look for solutions.

Scratch beneath the surface and you will find a business that is solid, but slightly contrary. We like to do things differently and constantly seek to evolve. We might have been around for a long time (our roots go back to 1901), but we are young in many ways, ambitious and going places.

Some people might say insurance is dull, but life at Hiscox is anything but. If that sounds good to you, get in touch.

Diversity and Hybrid working

At Hiscox we care about our people. We hire the best people for the job and we’re committed to diversity and creating a truly inclusive culture, which we believe drives success.

We have also learned over the past few years that working life doesn’t always have to be in the office, and now it is safe to do so we have introduced hybrid working to encourage a healthy work life balance.

This hybrid working model is set by the team rather than the business to enable you to manage your own personal work-life balance. We see it as the best of both worlds; structure and sociability on one hand, and independence and flexibility on the other.

 
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