Dolat Capital Market Pvt. Ltd. is a multi-strategy trading firm, dedicated to producing superior returns adhering to mathematical and statistical techniques. We trade actively in all Asset classes: equities, futures, options, commodities, currencies and fixed income taking advantage of our ultra-low latency infrastructure. Our low latency infrastructure is in C++, one of the most competitive in terms of latency.
About the job
We are seeking equally empirical and imaginative thinkers to join our team. Scientists in the true sense, our quantitative research associates navigate the full research process. You will explore a breadth of challenges, in pursuit of a mission that entails:
- Contributing to original research on quantitative indicators/models that drive the construction of high frequency trading strategies, that we trade in production.
- Developing trading strategies, from idea generation and data collection to analysis and model creation.
- Applying quantitative techniques and market intuition to large, often novel or unconventional, datasets and cultivate areas of expertise along the way.
- Advancing existing initiatives and opening opportunities to pursue new, previously unexplored research topics.
- The incumbent shall work in a fast-paced, multi-tasking environment, analyzing large amount of data and developing prediction algorithms / regression models and implementing them in C++, R, Matlab and python environments.
- He / She shall be a part of a team that works in a lab environment that use machine-learning, applied mathematics, and techniques from modern statistics to develop and refine models of the financial markets, and to develop high frequency trading algorithms based on those models.
- Applying analytical and simulation techniques to analyze model performance.
Must haves:
- A strong academic record with preference for a master’s/Ph.D. degree in a quantitative discipline – computer science, mathematics, physics, statistics, or a related discipline.
- A demonstrated capacity to do first-class research & experience in tackling indepth research projects.
- Strong computer programming skills and experience working with data.
- Understanding in at least some of the following areas: time-series analysis, statistical estimation, Bayesian techniques, scenario analysis, numerical optimization and optimal control.
- Creativity, solid analytical skills and attention to detail.
- The ability to communicate complex ideas clearly.
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