State Street’s Artificial Intelligence and Financial Engineering is a global award-winning team. It has the mission to explore, enable and exploit artificial intelligence, machine learning, natural language processing, image recognition, and cognitive computing at scale for countless use cases across Alpha/CRD, Global Services, Global Advisors, Global Markets business lines, and corporate functions. The team is envisioned to have a mixed of intelligence technology, data science, quantitative modeling, financial engineering, and software engineering capabilities. The team has solved operational, and client experience related use cases and is making into investment and risk management related domains such as market movement, sentiment analysis, valuation, investment strategy, fund innovation and so on. This team has engaged the business to explore, prototype, and solution use cases while also building out a portfolio of foundational AI/ML models as service and products in the public cloud.
We are seeking a motivated and results-oriented data scientist to support the development of an AI-driven product. The ideal candidate will contribute to building scalable solutions for data processing, data feature design and implementation, AI/ML model design and implementation, AI/ML result reasoning and interpretability, etc., while collaborating closely with data engineers, financial engineers, product managers and stakeholders. The role is ideal for early-career professionals looking to gain hands-on experience in AI, big-data processing and product development.
Responsibilities
- Responsible for low level AI/ML model and algorithm design, development, and validation by converting financial data and models to mathematical and computer science level design and implementation with consideration of space and time complexity
- Integrate, customize, and train well-established model and algorithm in open-source libraries to solve financial market problem and perform validation and bug fixes
- Monitor model performance and continuously improve algorithms for accuracy, efficiency, and interpretability
- Collaborate with a team of data scientist, data engineer, financial engineer, software engineer, and model validation/QA engineer with the aim of product/project deliveries
- Support IT integration, QA/UAT and deployment of AI micro services, operationalizing and productizing resulting models and AI solutions
Qualifications:
- Master's or Ph.D. degree (preferably in Computer Science, Mathematical Finance, Statistics, Data Science, and Financial Engineering)
- Solid background in mathematics including but not limited to statistics, probability theory, PDE, linear algebra, stochastic calculus, differential equations etc.
- 3+ years of solid modern, object-oriented or functional programming and design experience (Python, C++, SQL)
- 3+ years of experience working as an AI/Data scientist with proven experience building and deploying ML models in production environments
- Strong proficiency in Python and common data science libraries
- Familiar with public cloud development environment like Azure AML or AWS SageMaker
- Familiar with major financial instrument, reference data, market data, investment and risk management concept
- Familiar with traditional machine learning (regression, decision tree etc.) and deep learning neural network (CNN, LSTM etc.)
- Result driven, detail oriented, technical attitude
Experience in any of the following is highly desirable:
- Behavioral, time sequence, and outlier detection modeling experience
- Linux / Bash scripting, structured and unstructured data management tools (Snowflake, PostgreSQL, Hadoop, etc.)
- Continuous integration & development environments and tools (GIT, Maven, Jenkins, etc.)
- Communication skills. The ability to communicate at the right level with all parties involved, including management and business stakeholders
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