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Actuarial Data Scientist

3 months ago

London, Greater London, United Kingdom The Emerald Group Ltd, Search and Selection Full time
Job Description

Our client is a leading independent consultancy that uses powerful analytics fused with human expertise to shape a more positive future. They provide market-leading capabilities across pensions and financial services, energy, health, and analytics. Their technology and analytics capabilities are fundamental to what they do, helping them power the possibilities that provide solutions for tomorrow.

Within the Insurance Analytics team they are passionate about applying the latest analytics techniques to actuarial work and are keen to work with people who share their passion. Their market leading analytics platform is used by some of the largest insurers in the world to assess over £150bn reserves.

Some of the things they have done so far include:

Using machine learning to automatically identify and highlight trends in insurers' data and deploying this to production using Azure

Analysis to assess the impact of key factors including weather, age of vehicle and driver region on the reserves of a large UK motor insurer

Building stochastic simulation models in R to support one of the largest reinsurance placements in the London Market

What's the role and what will you be doing?

Due to the success of the team, they are looking for someone to help them develop further and deliver more consulting analytics projects to insurers. They are looking for individuals with experience in delivering analytics projects to non-life insurers in Python. Experience with R and/or working with cloud computing (preferably Azure) would be beneficial but is not essential.

Specifically, you will be:

Working within their dynamic team of actuaries, data scientists and software developers

Using your insurance, data science and actuarial knowledge to design and implement analytics solutions to non-life insurance problems, using modern techniques whilst considering practicalities such as the amount of data available and explicability

Working on the development and implementation of new features including delegating work to more junior members of the team. Day to day, this will involve writing and reviewing Python code in Pycharm, using version control, writing tests, and deploying code to production in Azure

Developing prototypes of new analytics solutions and supporting the wider Insurance Consulting team in using these solutions in consultancy projects (e.g. new analytics solutions, analysing large datasets and building automated processes)

Working on consulting projects, primarily those requiring Python and/or analytics techniques, but also occasionally working on broader projects where necessary, these projects would be across pricing, reserving, capital and claims

Training more junior members of the team in Python and applying statistical and machine learning techniques to solve business problems effectively

Planning and executing work in reasonable timescales to stipulated or agreed deadlines

Checking work you have completed, and/or reviewing work completed by more junior members of the team, including performing reasonableness checks using your knowledge of non-life insurance and actuarial work

What are they looking for?

To transform actuarial work you need to have a good understanding of the work actuaries do for insurers, you don't have to be an actuary though

You're happy working in Python, ideally you have significant experience using Pandas in Python. Experience using R and R'sTidyverse packages would be beneficial but is not essential

Track record of applying statistical and machine learning techniques to solve business problems for non-life insurers

Experience working in a controlled coding environment, including using version control and a testing framework

Excellent presentation and communication skills, able to give concise summaries of analytics solutions, but also comfortable answering detailed technical questions