Quantitative Research Analyst
4 weeks ago
At Dolat Capital, we are dedicated to producing high returns using mathematical and statistical techniques. 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 an empirical and imaginative thinker to contribute to original research on quantitative indicators/models that drive the construction of high-frequency trading strategies.
Key Responsibilities:
- 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
- Automate human-decision based trading strategies; prototype algorithmic trades from trading ideas
Requirements:
- A strong academic record with a preference for a master's/PhD 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 in-depth 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.
- A curiosity for model development and experience handling large data sets
- Strong problem-solving and statistics skills
- The proactive ability to take the lead on assignments and deliver practical research results in a timely manner
- Can advocate for your beliefs in a concise and effective way with the team
- Creativity, solid analytical skills and attention to detail.
- The ability to communicate complex ideas clearly.
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