Quantitative Financial Research Analyst

1 month ago

Mumbai, India Mirae Asset Global Investments Full time

About Us: Wealthspot, a subsidiary of Mirae Asset Financial Group, is a global quantitative asset management company focused on AI/ML-driven investment strategies. The company is headquartered in the United States and has offices in South Korea and India.


Position Summary: We are looking for a talented and driven Quantitative Financial Research Analyst with a strong background in machine learning and AI techniques. The ideal candidate will have 5+ years of experience in the financial industry and proficiency in financial data analysis, machine learning algorithms, and predictive modeling. Additional expertise in database management and SQL queries is highly preferred.


Key Responsibilities:

  Collect, process, analyze, and interpret large datasets from various financial sources to derive meaningful insights and actionable recommendations.

  Conduct in-depth financial research and analysis using advanced machine learning and AI techniques to identify trends, patterns, and potential opportunities in the market.

  Develop, verify, maintain, and enhance predictive models to support investment strategies and decision-making processes.


Required Qualifications:

  Bachelor’s degree in Finance, Economics, Computer Science, Data Science, or a related field. A Master’s degree is a plus.

  5+ years of experience in financial analysis, with a focus on applying machine learning, deep learning, and other AI techniques

  Proficiency in programming languages such as Python or R with strong knowledge of machine learning and AI libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

  Solid understanding of financial markets, instruments, and investment strategies.


Preferred Qualifications:

  Certification in financial analysis (e.g., CFA) or data science (e.g., Coursera, edX, etc.) is a plus.

  Experience with financial data services and platforms (e.g., Bloomberg, FactSet, etc.).

  Experience with database management systems


Skills:

  Statistical analysis including Time series analysis and forecasting

  Machine learning algorithms (e.g., regression, classification, clustering)

  Deep learning techniques and neural network architectures

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