Quantitative Research Analyst

Founded in 1971, Dolat Capital is a multi-strategy quantitative trading firm, dedicated to producing high returns using mathematical and statistical techniques. We trade actively in various asset classes using our ultra-low latency trading infrastructure.

At Dolat, quantitative research is the foundation for our trading strategies. We conduct a quantitative analysis of market data to uncover relationships and identify historical trends for exploiting anomalies in the market. Our quantitative research team develops mathematical and statistical models, based on historical data, to represent markets and behavioural patterns.

As a Quantitative Researcher, you will develop mathematical models using statistical methods to build fully automated trading systems & strategies. Our research team collaborates on idea generation, strategy development, and encourages independent exploration of novel ideas.

We have a group of bright quantitative researchers and analysts from various scientific disciplines who have built an array of analytical tools, to help us design, develop and run our quantitative strategies in financial markets.

We are seeking equally empirical and imaginative thinker to join our team.

Role & Responsibility

• 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
• Extract predictive signals from financial data through statistical analysis methods
• Assist software developers to translate research strategies into production software
• Optimize the order execution and risk management of our trading system
• Analyze a large amount of data and develop prediction algorithms / regression models and implement them in C++, R, Matlab and python environments
• Formulate and apply mathematical modelling techniques to enhance existing trading strategies and perform innovative new research with the goal of identifying and capturing trading opportunities
• Automate human-decision based trading strategies; prototype algorithmic trades from trading ideas
• Applying analytical and simulation techniques to analyze model performance

Must Haves