Lead Pricing Data Scientist

Zego is a commercial motor insurance provider that powers opportunities for businesses, from fleets of just two vehicles to global enterprises, and for individual drivers and riders. Its mission is to provide businesses and people with insurance they control, saving them both time and money.

The problem that exists is that in an ever-changing world, traditional insurance holds businesses back. Zego, on the other hand, helps businesses to unlock their full potential by putting them in control. Using smart technology and sophisticated data sources, Zego gives businesses the power to monitor and improve their driving performance over time, enabling them to save money by retaining a great price for their cover. It also helps businesses save time, making the administrative side of things easy and the claims process effortless.

Since its inception in 2016, Zego has grown to support businesses in the UK and across Europe and has forged partnerships with businesses such as BP, Amazon and Uber. Zego has also raised $280 million in funding and was the first UK insurtech to be valued at over $1 billion.

Overview of the Pricing Function

The Pricing function at Zego has recently undergone a transformation. We now have a function that consists of Actuaries and Data Scientists working in Squads. We have two main squads which are Live Pricing Squad and Features & Models Squad.

These two squads are responsible for delivering pricing for Zego’s diverse portfolio of products. This role will be working directly with the Pricing Leadership team at Zego.

The Role

The Pricing Function is looking for a motivated Pricing Data Science Lead to influence and play a pivotal role in building out our modelling capabilities. This role will be a mixture of hands-on delivery of projects mixed with coaching and mentoring junior members of the team.

The hands-on work will involve development of new insurance pricing models, leveraging novel sources of behavioural data and state-of-the-art machine learning techniques. This is a dynamic role where you will work closely with Data Scientists, Machine Learning Engineers and Actuaries to improve Zego’s risk identification and selection capabilities.

The role is suited to a candidate with existing data science experience, ideally in the areas of insurance modelling, predictive analytics, pricing and risk management. You will have proven skills using a programming language such as Python , skill with SQL, and an understanding of good development practices (git, code review, documentation). You will be given the support and backing you need to develop your skills, including on the job training, L&D budget, and a personal career development plan.

What you will be working on

• You will dive into the heart of Zego pricing efforts and help to build market leading pricing analytics and risk prediction capabilities.
• You will use modern tools, methods and techniques to develop advanced algorithms to take smart and instantaneous decisions and promote automation in different areas.
• You will work with various types and diverse datasets, including claims, driver behaviour, shift and trip information, traffic, weather, telemetry, geospatial data, web and smartphone sensors.
• You will conduct pre- and post-deployment impact analysis to quantify the success of new strategies and pricing implementations.
• You will contribute to improving Zego’s understanding of how driver behaviour relates to actuarial risk and how Zego’s can leverage the insights to disrupt how the industry currently operates.
• You will define and improve rigorous reproducible research practices to maintain excellence in all you do.
• You will constantly generate new research ideas, building a case and presenting your findings to propel capability forward.
• You will work with a diverse team of collaborative data professionals who enjoy technical discussions, learning new methodologies, and helping each other improve through feedback and shared research tools.

About you

• You have BSc/BA in Mathematics, Statistics, Engineering, Computer Science or similarly quantitative disciplines.
• You have 5+ years of experience as a data scientist, preferably in pricing, risk or insurance related roles.
• You are strongly proficient working with and querying structured data using SQL.
• You are highly experienced in Python applied to data analysis and predictive modelling.
• You are well-versed in modern machine learning tools and libraries such as Scikit-learn and Statsmodel
• You are familiar with common statistical tools and methods employed in insurance analysis, such as generalised linear models (GLMs), classification and regression trees (CARTs), ensembling methods, and clustering approaches as well as demonstrable knowledge in Bayesian statistics.
• You have experience and enthusiasm for reproducible research techniques including version control (geg. Git & Github etc.).
• You have outstanding eye to detail and take care to make sure that your work is accurate and effective.
• You have the ability to present complex information in an easily digestible format, appropriate for the audience.
• You are a lifelong learner; as technologies and techniques are constantly evolving, you are proactively pushing yourself to develop your skills and knowledge.
• You are resilient to change and use a holistic view of the business to ensure your goals are aligned and your work has impact.