Senior Research Analyst, Data Analytics

As a Support Analyst at the leading alternative asset manager, your role will involve supporting investment portfolio reporting and conducting quantitative analyses. You will play a key role in developing and enhancing workflow efficiency through automation. Additionally, you will be responsible for assisting in the development, calibration, prototyping, and documentation of risk models. Your contributions will also extend to preparing materials for clients and senior management, and collaborating on the establishment of a robust risk management framework and analytics across portfolios. Key Responsibilities: - Support investment portfolio reporting and quantitative analyses - Develop and enhance workflow efficiency through automation - Assist in the development, calibration, prototyping, and documentation of risk models - Prepare materials for clients and senior management - Contribute to the development of a robust risk management framework and analytics across portfolios - Analyze time series data using quantitative techniques and machine learning models to identify trends or errors/exceptions - Develop and maintain dynamic dashboards in risk reporting Qualifications Required: - Experience in data science, machine learning, and quantitative modeling - Proficiency in programming languages such as Python and SQL, and libraries like Pandas, Numpy, Matplotlib - Experience with Amazon SageMaker and a strong command of Excel - Familiarity with web scraping using libraries like Selenium and Requests - Basic knowledge of BI tools like Tableau or Sigma Computing - Experience with risk analytic platforms such as FactSet, Risk Metrics, or Bloomberg In addition to the above responsibilities and qualifications, the ideal candidate should have 3-7 years of relevant experience in the field. As a Support Analyst at the leading alternative asset manager, your role will involve supporting investment portfolio reporting and conducting quantitative analyses. You will play a key role in developing and enhancing workflow efficiency through automation. Additionally, you will be responsible for assisting in the development, calibration, prototyping, and documentation of risk models. Your contributions will also extend to preparing materials for clients and senior management, and collaborating on the establishment of a robust risk management framework and analytics across portfolios. Key Responsibilities: - Support investment portfolio reporting and quantitative analyses - Develop and enhance workflow efficiency through automation - Assist in the development, calibration, prototyping, and documentation of risk models - Prepare materials for clients and senior management - Contribute to the development of a robust risk management framework and analytics across portfolios - Analyze time series data using quantitative techniques and machine learning models to identify trends or errors/exceptions - Develop and maintain dynamic dashboards in risk reporting Qualifications Required: - Experience in data science, machine learning, and quantitative modeling - Proficiency in programming languages such as Python and SQL, and libraries like Pandas, Numpy, Matplotlib - Experience with Amazon SageMaker and a strong command of Excel - Familiarity with web scraping using libraries like Selenium and Requests - Basic knowledge of BI tools like Tableau or Sigma Computing - Experience with risk analytic platforms such as FactSet, Risk Metrics, or Bloomberg In addition to the above responsibilities and qualifications, the ideal candidate should have 3-7 years of relevant experience in the field.