Quantitative Analyst | Quantitative Research Analyst

Role DescriptionWe are looking for a highly analytical and quantitative professional to support quantitative analysis, financial research, statistical modelling, and data-driven decision-making. The role combines quantitative research, mathematical modelling, financial data analysis, and strategy development to generate insights and support investment and business decisions.Key responsibilities include collecting, cleaning, and analyzing large datasets, developing statistical and mathematical models, conducting quantitative research, and identifying meaningful patterns, trends, and signals. The role will involve testing hypotheses, performing historical analysis and backtesting, evaluating model performance, and supporting the development and refinement of quantitative strategies.The successful candidate will collaborate with researchers, investment professionals, developers, and other stakeholders to develop analytical solutions and improve research methodologies. The role also involves documenting research findings, monitoring model performance, assessing model limitations and risks, and applying rigorous quantitative methods to support investment analysis and data-driven decision-making.QualificationsStrong understanding of quantitative analysis, statistics, financial markets, mathematical modelling, and data analysis.Strong proficiency in Python, R, MATLAB, or other quantitative programming languages.Solid knowledge of probability, statistics, linear algebra, calculus, and numerical methods.Ability to work with large and complex datasets and extract meaningful insights.Familiarity with financial instruments, investment concepts, market behavior, and portfolio analysis.Knowledge of statistical modelling, forecasting, hypothesis testing, and quantitative research techniques.Understanding of backtesting, factor analysis, signal generation, and model validation is preferred.Strong proficiency in SQL and familiarity with databases or data-processing tools is an advantage.Knowledge of machine learning, time-series analysis, optimization, or econometric methods is beneficial.Strong analytical, logical, critical-thinking, and problem-solving skills.Ability to communicate complex quantitative concepts and research findings clearly.Strong attention to detail and commitment to data quality, model integrity, and analytical accuracy.Curious, rigorous, and research-oriented mindset with a strong interest in quantitative methods, financial data, and continuous innovation.