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Technical Modelling Analyst

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Req ID:
R-12260
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Category:
Actuarial
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Location:
Bromley; Leeds

Direct Line Group is one of Britain's leading general insurers, offering millions of customers decades of experience and knowledge. In the history of modern insurance, there has never been a bigger time for change than now, and we work hard to make sure our well-known brands –Direct Line, Churchill, Privilege, NIG and Green Flag are making insurance easier and better value for our customers. We know we can’t do this without our phenomenal people who we appreciate for ideas and thinking as well as results because that’s how we can achieve amazing things!

Commercial Lines is an increasingly meaningful part of Direct Line Group’s success story and there are ambitious plans to deliver further performance improvements via a pricing transformation program that entails using improved risk, geo and demand models, having an improved data infrastructure, and having access to an advanced suite of analytical tools.

What we are looking for

We have a great opportunity to join our Commercial Modelling team supporting in delivering technical models for all Commercial Lines products across all channels.  You do not need to have extensive modelling experience for this role as training can be provided but a numerical background is beneficial.

  • Assist in delivering and planning all model recommendations and their resultant implementation as well as actively contributing to and assisting in defining the longer term strategy for the modelling team.

  • Update and develop technical models to enable the business to both price effectively and to manage risk through model outputs.

  • Assist in the delivery of technical analysis into new and innovative insights. Help to develop and improve the processes required.

  • Investigate the potential of non-GLM techniques (supervised and unsupervised models) and how they can be used in conjunction with existing models.

  • Strive continuously to improve the statistical validity and efficiency of all modelling, projection processes and techniques.

  • Interact actively with peers in other areas of DLG to actively share knowledge, models and techniques and ensure learnings are embedded into future strategy and communicated effectively across the team.

  • You will be an effective communicator at all levels and be able to demonstrate strong numerical and statistical skills. You will also have the ability to present modelling inference and statistical findings in layman terms to a wide range of stakeholders including Pricing & Underwriting personnel. Being a team player is key but you need your own initiative to be able to progress work independently.

  • You should be educated to a numerical degree. Prior experience of traditional and/or statistical modelling will be desirable. Knowledge of machine learning AI using R/Python, Alteryx, Tableau and SQL will also be beneficial to you in this role.

Ways of Working

Here at Direct Line Group, we recognise the importance of flexibility, not only in our personal lives but also in the way we work. Our mixed model way of working offers a ‘best of both worlds’ approach combining the best parts of home and office-working, offering flexibility for everyone.

How much you’ll be in the office depends on your role, and we’ll consider the flexible working options that work best for you. You can find out more about our flexible working approach or please get in touch with the team to discuss. 

Life at DLG

Direct Line Group is an equal opportunity employer. We value diversity and we’re committed to making DLG a truly inclusive place to work.  

We recognise and embrace that people work in different ways and we’ll always adapt as much as possible so you have the best and most comfortable working environment that we can offer. We know you’re more than a CV, and the things that make you, you, can bring real potential to DLG. 

If you need us to make any adjustments to our recruitment process, speak to our recruitment team who will be happy to support you.  

#L1-SM2

#LI-Hybrid

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