Machine Learning Engineer
Core
Design, prototype, and implement data processes and machine learning models to support quantitative research and discretionary trading strategies.
Role type
Machine Learning Engineer (Buy-side Quant)
Builds
Live models processing billions of market data ticks, news, and alternative data for the fund's trading strategies.
Domain
Alternative Investment Management / Quantitative Finance
Deliverable
production ML models
Required skills
Machine Learning, Statistics, Time Series Forecasting, Panel Data Analysis, Scientific Computing, Optimization, Distributed Data Processing, Python, C++, SQL, Spark/Scala, Containerization
Preferred skills
Production code for multi-client systems, Full-stack development
Technologies
Python, C++, Spark, Scala, SQL, Containerized environments
Responsibilities
Develop time series and forecasting models to support quant strategies, dive deep into multiple data sets to understand relationships, leverage state-of-the-art ML and advanced statistical methods to produce data sources for the fund, work closely with Quant Researchers and Portfolio Managers to solve data problems.
Seniority
Mid-level, hands-on IC