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About the role
As an Associate Quantitative Analyst at QuantumStreet AI, you will have the opportunity to work at the forefront of finance and data science in the Investment Science Lab in Bengaluru. Your role will involve contributing to projects that manage multiple billions of USD in assets, collaborating with cross-functional teams, and utilizing cutting-edge tools to enhance portfolio performance and risk assessment for our esteemed clients. Key Responsibilities: - Analyse structured and unstructured financial datasets to extract meaningful insights. - Build and implement predictive models, statistical analyses, and machine learning solutions for investment optimization and wealth management strategies. - Work on time series forecasting, unstructured data analysis, knowledge graphs, risk modelling, and portfolio performance analytics. - Ensure data quality, cleansing, and integration from various sources to work with large financial datasets. - Conduct exploratory data analysis (EDA) and hypothesis testing. - Develop and evaluate new models for forecast and optimization. - Create optimized portfolios tailored to specific client needs. - Analyze the performance of portfolios and generate material for client communication. Qualifications Required: - Excellent skills in Statistics, Data Science, and Investment Analysis. - General awareness of financial markets and the global economy would be advantageous. - Proficiency in programming languages, especially Python, SQL, and model deployment pipelines is expected. As an Associate Quantitative Analyst at QuantumStreet AI, you will have the opportunity to work at the forefront of finance and data science in the Investment Science Lab in Bengaluru. Your role will involve contributing to projects that manage multiple billions of USD in assets, collaborating with cross-functional teams, and utilizing cutting-edge tools to enhance portfolio performance and risk assessment for our esteemed clients. Key Responsibilities: - Analyse structured and unstructured financial datasets to extract meaningful insights. - Build and implement predictive models, statistical analyses, and machine learning solutions for investment optimization and wealth management strategies. - Work on time series forecasting, unstructured data analysis, knowledge graphs, risk modelling, and portfolio performance analytics. - Ensure data quality, cleansing, and integration from various sources to work with large financial datasets. - Conduct exploratory data analysis (EDA) and hypothesis testing. - Develop and evaluate new models for forecast and optimization. - Create optimized portfolios tailored to specific client needs. - Analyze the performance of portfolios and generate material for client communication. Qualifications Required: - Excellent skills in Statistics, Data Science, and Investment Analysis. - General awareness of financial markets and the global economy would be advantageous. - Proficiency in programming languages, especially Python, SQL, and model deployment pipelines is expected.