Senior AI/ML Scientist, Officer

$75,000 - $120,000/Yr

2001 SSB&T - Irvine, CA

Full-time - Mid Level

Irvine, CA

About the position

The Senior Data Scientist - Officer at State Street's Artificial Intelligence and Financial Engineering team is responsible for designing, developing, and validating quantitative financial models and algorithms. This role involves collaborating with a diverse team to explore and implement AI services that address various financial market challenges, focusing on operationalizing and productizing AI solutions in a cloud environment.

Responsibilities

• Responsible for low level 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 known model and algorithm in open-source libraries to solve financial market problems and perform validation and bug fixes.
• Work with a team of data scientists, machine learning engineers, financial modelers, software engineers, and model validation/QA engineers.
• Support IT integration, QA/UAT and deployment of AI micro services, operationalizing and productizing resulting models and AI solutions.
• Support production issues pertinent to model and algorithm including the ones used in open-source libraries.

Requirements

• Master's degree required (preferably in computer science, mathematical finance, and financial engineering).
• Solid background in mathematics including but not limited to statistics, probability theory, PDE, linear algebra, stochastic calculus, differential equations, etc.
• 1+ years of solid modern, object-oriented or functional programming and design experience (Python, C++, SQL).
• 1+ years of experience working as an AI/Data scientist.
• Familiar with public cloud development environments like Azure AML or AWS SageMaker.
• Familiar with major financial instruments, reference data, market data, investment and risk management concepts.
• Familiar with traditional machine learning (regression, decision tree, etc.) and deep learning neural networks (CNN, LSTM, etc.).
• Result driven, detail oriented, candid attitude.

Nice-to-haves

• 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.).
• Strong communication skills to interact with management and business stakeholders.

Benefits

• Tools to help balance professional and personal life.
• Paid volunteer days.
• Access to employee networks for connection and support.