Senior Transition Risk Modeller - Cambridge, United Kingdom - IAC

    IAC
    IAC Cambridge, United Kingdom

    1 week ago

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    Description

    Exciting opportunity to join this Series-B risk modelling and analytics organisation on the next phase of their growth journey. They help dozens of household brands and global players with modelling and quantification of risk and transition planning.

    In this role, you will help develop and maintain a suite of environmental and risk models. This role will have a primary focus on climate-related transition risk modelling and transition planning. This includes developing new models and methods to quantify economic, technological, and social dimensions of a low-carbon and nature positive transition, as well as assessing the business initiatives that will be required for this transition to occur. You will be a thought leader within the team and apply your existing knowledge across nature and climate to build the next generation of data driven models.

    You will be part of a talented team of modelers, economists, data scientists, and software engineers wrangling with complex datasets, conducting analytics and building rigorous models to help quantify the probability, consequences and financial impacts of nature and climate risk scenarios. Your work will generate new insights through the visualization and representation of outputs to solve challenges related to the quantification of environmental risks to business.

    You will have a numerical background and demonstrable experience with a programming language (Python preferred) and an ability to organize and interpret datasets and present results and insights. Expertise in relevant scientific topics related to climate change, such as economics, energy, finance, risk analysis and/or quantitative modelling is essential.

    An in-depth understanding of company carbon accounting and impact assessments, and sustainability reporting frameworks such as TCFD, CSRD, etc. is desirable as is experience of macroeconomic modelling techniques, such as econometrics or environmentally extended input-output (EEIO) models, and their application to real-world problems.

    This is a passionate team with huge amounts of talent and leaders who really care about the development and happiness of the team.