Python Data Engineer for Quant Strategies Research

Role description

Quant strategies team needs a solid Python engineer to work with their chief researcher on the build-out of a data engineering pipeline that will be used for portfolio construction, research and NLP processing. Python engineer will be embedded in the Quant strategies team and will get exposed to investment mechanics, modelling and portfolio optimization.

Responsibilities

• Be the sole Python data engineer to architect, design and implement a research-driven ML data pipeline for financial data
• Leverage best practice tools for real-time data (Kafka, Airflow, etc) and implement all tools and libraries for data validation and monitoring
• Build out the NLP processing platform to help deliver market insights in a simple-to-understand language

Requirements

• Bachelor’s degree (preferably in computer science, or appropriate technology field with Math/Statistics
• Excellent large scale Python (NumPy, Pandas) experience building real-time data pipelines for researchers/quants
• Understanding of computation cost optimization for backtesting of complex datasets
• Excellent communication skills to face off with researchers and quants to translate data needs into deliverables