Location: UK: London/Reigate/Leeds

Start Date: asap

Opportunity: Supported hiring into Fixed Term Contract

Closing date for applications:  Apply ASAP

** This role is now closed for applications **

As part of the Diversity Project Supported Hiring initiative, Willis Towers Watson welcomes professionals who have taken an extended career break to apply for a Financial Modelling position.

A successful candidate who has taken a career break of 18+months will receive coaching support through the transition period from Women Returners. You may have taken time out for childcare or eldercare, for relocation, or for other reasons. You may have been working on a small-scale basis to fit around your other commitments or have not done any paid work for a number of years.

About the Role

Willis Towers Watson are looking for someone with financial modelling experience to join their team.  This is a fixed term (12 months with the possibility to extend) role which will include a mixture of project and client-facing work using their flagship STAR RW product, a real world economic scenario generator (ESG). They have an ambitious programme of research and development planned to enhance the calibration process and core mathematical models underlying the ESG, while also continuing to support their clients.

You will receive on-the-job training and support to familiarise yourself with their business, models and systems.  You will quickly be able to participate in regular calibration of our models, preparing client deliverables and responding to client queries.  You will also have the opportunity to participate in research projects and model testing and implementation, and will provide guidance to more junior colleagues.

This role offers flexibility in working pattern so please do discuss your requirements on application.

The Requirements

  • Candidates are expected to have a foundation in applying mathematical techniques to financial modelling, with some knowledge of areas such as statistics, probability theory, time-series analysis or stochastic calculus
  • Prior practical experience of stochastic modelling, particularly the use and calibration of ESGs, in the context of insurance or pensions would be an advantage
  • Basic knowledge of economics and financial markets including typical asset classes used by long-term investors, eg fixed income, equity
  • The ability to build relationships and interact with clients and communicate technical information to a non-expert audience, both internally and externally
  • Familiarity with statistical computing packages (eg Matlab) or first experience in programming languages (eg C#).

The Role

  • Rapidly gain understanding of the models and tools underlying STAR RW
  • Support development of the model and calibration process
  • Develop knowledge of asset classes used by our clients and modelling approaches used in STAR RW
  • Assist with managing STAR RW clients, through responding to client queries, delivering training and undertaking appropriate investigations if necessary
  • Participate in other business-as-usual tasks including regular calibration of our models and preparing client deliverables
  • Guide junior members of the team

You will be working in a small, collaborative team and you will be supported to apply your current skills and experience to their business.

About Willis Towers Watson

Willis Towers Watson is a leading global advisory, broking and solutions company that helps clients around the world turn risk into a path for growth. With roots dating to 1828, Willis Towers Watson has 40,000 employees serving more than 140 countries. They design and deliver solutions that manage risk, optimize benefits, cultivate talent, and expand the power of capital to protect and strengthen institutions and individuals. Their unique perspective allows them to see the critical intersections between talent, assets and ideas – the dynamic formula that drives business performance. Together, they unlock potential. Learn more at willistowerswatson.com.

To Apply

Apply through the online portal here 

Please apply asap.

Please show your career break clearly in your CV.