Linear Quantitative Research
J.P. Morgan’s Global Quants Group in Mumbai was set up in 2013 as an extension of the Firm’s global quants teams around the world. It is a fast growing team covering multiple asset classes across geographies. It provides in-depth knowledge that is behind our Investment Banking, Structuring, Sales & Trading and Research businesses around the globe. Deeply integrated with our Investment Banking business, the team facilitates deals and transactions by providing vital research and insight.
This position is a Quant profile to support the activities of the Quantitative Research Group (cross asset classes) & Linear Quantitative Research (LQR) globally sitting out in Mumbai. The QR team in Mumbai plays a critical role in providing effective, timely and independent assessments of the Firm’s booking models of exotic structures and also help in developing new models for structures as and when necessary.
Linear Quantitative Research (LQR) is an expert quantitative modeling group in J.P. Morgan, an unchallenged leader in financial engineering, statistical modeling and portfolio management. With more than 30 researchers worldwide, LQR partners with traders, marketers and risk managers across all products and regions.
The LQR team is responsible for mainly the following:
- Developing mathematical models for systematic quantitative trading strategies, for example, Electronic Trading Algorithms, Index Arbitrage, Statistical Arbitrage, portfolio optimization, flow recommendation research, IOI and Market Making.
- Carrying out market microstructure research and writing white papers
Candidates should be able to:
- Handle high frequency data /Big data and develop statistical model on the same
- Research, design, implement, and evaluate machine learning approaches and models for the domain
- Work on short term price predictive , alpha and portfolio optimization models
- pre/post trade Analytics(including market microstructure research) for execution Algorithm /risk trading
- Look into new research on the field and assess the applicability
- Research as well as implement their Ideas
- Python and q/Kdb experience is a plus
- Have mastered advanced mathematics and statistics ( probability, econometrics, optimization and Machine Learning)
- Algorithms and Data Structures knowledge
- Earned a Master or equivalent degree program in math, statistics, econometrics, financial engineering or computer science
- Exceptional analytical, quantitative and problem-solving skills
- Good communication and interpersonal skills
Ideal candidates for these positions would be a graduate/post-graduate from a premier college or institute. A computer science or mathematics background will be most suitable.
J.P. Morgan’s Global Quants Group provides a challenging work environment and excellent opportunities to learn and grow both at the Quants Group and in the Firm’s global network.