Role & responsibilities Conduct rigorous quantitative analyses on financial data to identify predictive patterns and signals forecasting equity returns. Develop, test, and refine predictive models to generate robust trading signals. Collaborate closely with the CIO, research team, and trading team to translate quantitative insights into actionable trading strategies. Manage the full lifecycle of research projects, from hypothesis formulation through back-testing, validation, and live implementation. Continuously monitor model performance, adapting strategies as market conditions evolve. Enhance and maintain existing quantitative research infrastructure, tools, and data processing workflows. Preferred candidate profile Bachelors degree in a quantitative discipline (Mathematics, Statistics, Physics, Computer Science, Electrical Engineering, or related fields) is required; a Master’s degree or Ph.D. in a quantitative discipline is strongly preferred. 3–5 years of direct experience in quantitative research or strategy development at a hedge fund, proprietary trading firm, or quantitative financial institution; prior experience specifically with equity markets and equity-oriented quantitative strategies is highly desirable. Demonstrated experience managing, cleaning, and analyzing medium to large datasets, including financial time-series and alternative datasets; familiarity with portfolio optimization techniques and risk modeling frameworks is beneficial. Solid foundation in statistical methods with practical experience applying statistical and machine learning techniques to financial data; experience integrating quantitative models into live trading environments is strongly preferred. Strong proficiency in Python programming, including libraries such as Pandas, NumPy, scikit-learn, and related data science tools. Exposure to distributed computing environments, databases, and cloud-based platforms for quantitative research is beneficial. Excellent analytical abilities, critical thinking skills, and meticulous attention to detail.
Role & responsibilities Conduct research on large, real-world datasets to develop and test trading strategies Perform statistical analysis and backtest investment signals across equity markets Design, develop, and validate predictive models using advanced quantitative techniques Collaborate with other team members to solve complex data and modeling challenges Present findings in a clear and structured format to both technical and non-technical stakeholders Stay abreast of the latest advancements in quantitative finance, machine learning, and data science Preferred candidate profile Strong programming skills in Python and/or C++ Experience in a data-driven research environment, preferably within the financial sector Proficient in building and testing algorithms for data processing and strategy evaluation Deep understanding of statistical modeling, machine learning, time-series analysis, and pattern recognition Hands-on experience with data cleaning, preprocessing, and SQL-based data querying Experience working with cloud storage solutions (e.g., Azure) Ability to perform independent research and take full ownership of projects Excellent communication skills, including the ability to present complex concepts clearly