Senior Data Scientist

Role overview

As a Senior Data Scientist, you will use your advanced analytical skills to:

• Lead the development of cutting-edge, bespoke machine learning predictive models, including risk pricing and classification and regression models
• Identify and create data solutions that create value
• Work collaboratively with the pricing and machine learning teams to provide insight across the business
• Your ideas and solutions will enable improvements to products, prices and processes giving [Employer hidden] a critical advantage in the increasingly competitive insurance market
• Identify and create solutions that leverage vast data assets and lead the development of bespoke machine-learning models to improve the underwriting performance of the Group.

Key Responsibilities:

• Develop and test modelling improvements for pricing models, particularly in motor. These might include improvements in hyper-parameter tuning methods, model performance, model stability and feature explainability
• Be the technical lead in the development of predictive models that solve business challenges through one-off analyses or bespoke modelling. Such work would include risk classification, such as area or vehicle classification, as well as predictive models for other business use cases such as conversion, retention or price optimisation
• Prototype ML solutions before handing to the ML team for implementation
• Conduct more advanced yet focused research and development to solve business challenges
• Work collaboratively with other teams to analyse and identify improvements to risk modelling and wider business challenges
• Use a wide range of data science and statistical techniques
• Research and leverage new and existing internal and/or external data sources
• Communicate results to key decision makers across the business
• Assist in the deployment and monitoring effort to ensure efficient implementation of the solutions created

Key Skills and Experience:

• PhD. or masters in statistics, data science or equivalent field or Degree with number of years of relevant experience
• Previous experience within data science
• Experience in insurance pricing and modelling
• Experience and detailed technical knowledge of GLMs /Elastic Nets, GBMs, GAMs, Random Forests, Neural Networks and clustering techniques
• Knowledge of statistics and distributions commonly used in insurance
• Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL)
• Proficient at communicating results in a concise manner both verbally and written

Behaviours:

• Motivated by technical excellence
• Driven to deliver iterative improvements in a timely fashion
• Team player
• Self-motivated with a drive to learn and develop
• Logical thinker with a professional and positive attitude