Analyst/Manager/AVP - Model Validation/Quant - Investment Bank - IIT/IIM

Top MNC investment bank hiring for Mumbai.

Candidate Qualification : PhD / M. Sc (Financial Engineering / Statistics / Mathematics) / M.Tech / B.Tech from (IIT / BITS / NITS) / IIM PG

Experience required - Minimum 1-8 years

Job Location - Mumbai

Designation - Analyst / Manager / AVP

Set Skills - Model Validation / Pricing model / Model Development / Quantitative developer / Quant developer

This opportunity is for a quantitative analyst role within the Quant team. The primary function is to perform detailed validation of models from across the team’s areas of responsibility.

Validation projects investigate all aspects of the models, covering their assumptions regarding the behavior of different asset classes, performance over different time scales, treatment of different products and risk types and their aggregation and use in the risk capital calculations.

Model validation reviews typically include:

- Participation in working groups addressing modelling issues and the model control environment

- Investigating key aspects of each model under review: the choice of model, its correct implementation and optimal use of the model

- Developing independent modelling for comparison with that under validation

- Reviewing the issues, assumptions and limitations of both the proposed and independent modelling approaches

- Backtesting alternative models to evaluate and compare their performance using historical simulations

- Reviewing findings with colleagues in different groups including model developers, risk managers and traders

- Developing appropriate controls to mitigate for model risk and residual uncertainty

- Documenting the testing performed: theoretical background, modelling issues, assumptions and limitations, testing performed, results and control implications

In conducting the reviews the analysts perform some computationally intensive work, including:

- Developing, maintaining and running test tools to investigate different aspects of the model

- Setting up and running historical backtesting scenarios

- Generating, extracting and structuring risk and value data from Front Office systems

- Implementing numerical algorithms and automating testing processes in VBA and C++