Quantitative Research- Market Capital - Vice President Alumni Career Site

3.0 - 7.0 years

0 Lacs

karnataka

On-site

Are you prepared for an exciting opportunity to be part of a dynamic team in a challenging setting As a Quant Modelling Vice President in the QR Markets Capital (QRMC) team, you will have a crucial role in implementing the next generation risk analytics platform. The main goal of the QRMC team is to construct models and infrastructure for managing Market Risk, including Value at Risk (VAR), Stress, and Fundamental Review of the Trading Book (FRTB). The QRMC team in India will play a significant role in supporting QRMC group's activities globally, collaborating closely with Front Office and Market Risk functions to create tools and utilities for model development and risk management. Your responsibilities will include working on implementing the next generation risk analytics platform, evaluating model performance, conducting back testing analysis and P&L attribution, enhancing the performance and scalability of analytics algorithms, developing mathematical models for VaR/Stress/FRTB, assessing the adequacy of quantitative models and associated risks, designing efficient numerical algorithms, and creating software frameworks for analytics delivery to systems and applications. To qualify for this role, you should hold an advanced degree (PhD, MSc, B.Tech or equivalent) in Engineering, Mathematics, Physics, Computer Science, or related fields and have at least 3 years of relevant experience in Python and/or C++. Proficiency in data structures, standard algorithms, and object-oriented design is essential. Additionally, you should possess a basic understanding of product knowledge across various asset classes such as Credit, Rates, Equities, Commodities, FX & SPG, and be interested in applying agile development practices. Strong quantitative and problem-solving skills, research skills, knowledge of basic mathematics like statistics and probability theory, good interpersonal and communication skills, and the ability to work in a team are also required. Attention to detail and adaptability are key attributes for success in this role. Preferred qualifications include experience with statistical and/or machine learning techniques in the financial industry, knowledge of options pricing theory, trading algorithms, or financial regulations, experience with multi-threading, GPU, MPI, grid, or other HPC technologies, excellent knowledge of data analysis tools in Python like Pandas, Numpy, Scipy, familiarity with advanced mathematics such as stochastic calculus, and understanding of front-end technologies like HTML, React, and integration with large data sets.,

Posted 2 days ago

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