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The Risk Engineering (RENG) team aims to measure the portfolio risk of both our clients and the firm. As a member of RENG, you will become an expert in various risk methodologies (Reg-T, Portfolio Margin) to build efficient, scalable systems from the ground up to quantify and manage these risks in real-time. This will involve leveraging AI and machine learning to provide answers about the portfolio, positions at client and aggregate levels, and intelligent automation for portfolio optimization.
Job Responsibility:
Architect new backend services and storage layers for risk based metrics
Optimize data models for storage and reporting
Design data ingestion pipelines in a distributed computing environment
Collect and break down requirements to produce technical designs
Collaborate with other tech teams, as well as business, operations, and compliance team members
Requirements:
At least five (5) years of professional engineering experience
5+ years of experience implementing scalable backend services with a statically-typed language (Go / Java preferred)
data-wrangling experience with common scripting languages (Python preferred)
familiar with common microservice architecture paradigms
experience designing and working with APIs to expose information externally
leverage strong communication skills to collaborate effectively with non-technical business stakeholders, product managers, and engineers
excited to explore new technologies and become an expert in our tech stack
Nice to have:
Financial risk modeling
Integration experience with MSCI, NASDAQ
Stream-processing experience, such as Beam and Flink
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