Quant Researcher, Investments, Vice President

About Fundamental Fixed Income Team

BlackRock’s active fixed income portfolio strategies stretch across a range of investment styles and segments of the fixed income universe.

The breadth and depth of our platform puts us in a strong position to potentially deliver attractive returns in various market environments. With a focus on alpha generation and risk management, the team uses a top-down view from lead portfolio managers and bottom-up expertise from our sector specialists.

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Responsibilities:

• Experience with advanced natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. Understanding of use and implementation of Vector Databases
• Ability to follow foundational programming principles (best practices, know about unit tests, code organization, basics of CI/CD etc.) and create a well-maintainable and tested codebase with relevant documentation.
• Implement prototypes for individual components of software or data science solutions and leverage basic data structures and algorithms in implementing solutions.
• Collaborate with peers within PMG and iHub India (MASS Labs, RQA Labs, AI Labs) to further research of use cases already in development within Firm wide initiatives.

Education and Qualifications/Skills:

• 7-12 years of experience
• Motivated team player and flexible in approach with ability to work independently.
• Technical skills in Python, including experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras. 
• Good understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory.
• Knowledge of at least one of the following domains: generative AI, statistical learning, optimization, NLP, deep learning, or time series analysis.
• Passion for solving interesting and relevant real-world problems (in Finance) using a data science and ML approaches.
• Strong analytical thinking skills with an ability to creatively solve business problems, innovating new approaches as needed.
• Data exploration and analysis skills (distributions, identify anomalies, create visualizations, etc.) and ability to implement algorithmic solutions in applied ML.
• Self-driven and results oriented team player with ability to collaborate effectively across geographies/time zones