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    Actuarial Data Scientist - London, United Kingdom - Lane Clark & Peacock

    Lane Clark & Peacock
    Lane Clark & Peacock London, United Kingdom

    3 weeks ago

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    Description

    Actuarial Data Scientist

    LCP is a leading independent consultancy that uses powerful analytics fused with human expertise to shape a more positive future. We provide market-leading capabilities across pensions and financial services, energy, health, and analytics. Our technology and analytics capabilities are fundamental to what we do, helping us power the possibilities that provide solutions for tomorrow. We strive to help our clients leverage the latest technology and analytics across a range of industries to stay at the forefront of data-driven and digital solutions.

    Within the Insurance Analytics team we are passionate about applying the latest analytics techniques to actuarial work and are keen to work with people who share our passion. Our market leading analytics platform, , was launched in April , and is used by some of the largest insurers in the world to assess over £bn reserves.

    Some of the things we have done so far include:

  • Using machine learning to automatically identify and highlight trends in insurers' data and deploying this to production in InsurSight 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, we are looking for someone to help us develop LCP InsurSight further and deliver more consulting analytics projects to insurers. We 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 our 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 in InsurSight, 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 (eg 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
  • Working within LCP's internal professional standards and external professional guidance

    • What are we 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

    • What's in it for you?

    Take a look at our

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