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Lead Quantitative Finance Specialist
1 month ago
State Street's Artificial Intelligence and Financial Engineering team is a strategic global unit under the direction of the company's management committee. The team explores, enables, and exploits artificial intelligence, machine learning, natural language processing, computer vision, and cognitive computing at scale for various use cases across Global Delivery, Global Advisors, Global Markets, and Global Exchange business lines.
The team has a diverse range of capabilities, including intelligence technology, quantitative modeling, data science, financial engineering, and software engineering. It has developed solutions for investment and risk management domains such as eFX trading, equity market movement, credit rating, sentiment analysis, valuation, investment strategy, fund innovation, operational, and client experience related use cases.
This role will engage with the business to explore, prototype, and implement AI services while building out a portfolio of foundational microservices in State Street's public cloud environment.
Key Responsibilities- Deliver assigned projects and/or products from model design, development, and validation to IT implementation and Quality Assurance
- Become an expert in low-level model and algorithm design, development, and validation by converting financial data and models into mathematical and computer science level designs
- Integrate, customize, and train well-known models and algorithms in open-source libraries to solve financial market problems and perform validation and bug fixes
- Build models and algorithms from scratch and perform validation, including loss function, optimization, and parameter tuning depending on the problem type and technique used
- Drive model rationalization, reusability, scalability, and implement modern MLOps
- Write model specifications with lead financial engineers and modelers about problem statements, assumptions, data input, methodologies, implementation frameworks, and test results
- Support IT integration, QA/UAT, and deployment of AI/ML microservices, operationalizing, and productizing resulting models and cognitive solutions
Compensation: $175,000 - $225,000 per year, based on qualifications and location
This role requires a Master's degree in computer science, mathematical finance, or financial engineering (preferably from a top-ranked university) and 7+ years of hands-on coding experience with classical AI/ML algorithms and familiarity with deep learning neural networks.
A strong background in mathematics, including statistics, probability theory, PDEs, linear algebra, stochastic calculus, differential equations, and experience with public cloud development environments like Azure AML, Snowflake, or AWS SageMaker are also required.
