A leading Global Insurance and Financial Services organisation is looking for candidates into Quant Model / Pricing Model Development.

The Job Responsibilities include:-

- Good understanding of financial markets, economics, developing financial models such as yield optimizers as well as an understanding of how data science techniques work.

- Ability to understand a business problem statement and translate it into a data science or quantitative investment problem independently or with minimal supervision

- Ability to understand results of data science models, evaluate them financially and wherever possible challenge the results to reduce bias/ confounding/ overfitting from a financial perspective

- Acting as an interface between investment specialists/ fund managers and data scientists to help each team understand, appreciate and start building on/ utilizing the work done by the other.

- Work and collaborate with colleagues and senior stakeholders in understanding and translating business problems into machine learning / modelling problems and to deliver cutting edge solutions

- To develop a range of quantitative, machine learning and statistical models to solve actual business cases within the M&G Plc universe

- Ability to influence and manage large virtual teams in a matrix structure

Essential

- 5 - 8 years experience of Quant Modelling / Data Scientist (using Machine Learning techniques) / financial modelling

- Advanced quantitative/ financial programming skills with at least one data related scripting language (e.g. Python is must ).

- Expertise in quantitative finance/ econometric techniques eg Portfolio Optimization, Stochastic modelling, Cash flow modelling, VAR, Statistics and machine learning techniques

- Keen mindset for financial analysis, economics and understanding markets, investment opportunities to build use-cases where data science led techniques could benefit the investment process

- Domain knowledge of Asset management / Investment Management industry

Desirable

- Advanced knowledge of OOP will be an advantage

- Experience with version control (git) and Agile software release cycle

- Hands on experience in executing and leading end to end projects for eg Interest Rate Modelling / Yield optimisation / Delinquency Modelling

- Experience in designing, experimenting with and evaluating highly innovative techniques for investment/ monitoring/ risk across business units such as Fixed Income, Equities and Real Estate

- Experience in working closely with business staff to optimize various business operations

- Experience in researching and implementing novel quantitative financial, machine learning and statistical approaches

- Business & Data Domain Knowledge (understanding of financial services)

- Experience with distributed computing frameworks such as Dask and/or Spark

- Experience with PyTorch, Tensorflow and/or other Deep Learning frameworks

- Experience using dockerized Python applications in production

- Demonstrable strong Machine learning/AI experience along with expertise in analytical tools like R and Python, SQL, Spark

- Track record of delivering results and strong ownership

- Working/ Research papers in the field of economics/ finance/ data science

- Experience working within BigData/Cloud environments (preferably Azure or AWS)

Qualifications: ( any one of the below )

- PhD level Academic qualifications (or similar work experience) in Investment Management

- BE / BTECH + CFA

- Masters Degree in Finance / economics from reputed institute

- Computer Science & Economics/ Econometrics or in a highly quantitative field

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