Hello everyone! Exos Financial is hiring a Quantitive Data Engineer to join our Quantitative Strategies group. Please DM me for more information or apply here. This is an NYC based position with a flexible WFH policy.
What is a Quantitative Data Engineer? A Quantitative Data Engineer is able to build durable pipelines for ingesting and transforming datasets from a variety of sources, in diverse formats, at multiple scales. Quantitative Data Engineers utilize distributed computing and cluster technology to accelerate research and deliver results faster. They are excited by the idea of leveraging emerging technologies to push the boundaries of quantitative finance.
Summary: We are an industry-leading, modern B2B financial services fintech looking for a Quantitative Data Engineer to assist in building out our quantitative research platform. The ideal candidate will have strong Python programming abilities, experience dealing with large and heterogeneous datasets, and the skills necessary to deliver high-quality software solutions in a fast-paced environment. This role will work closely with quantitative researchers to design and support advanced research capabilities, as well as our data engineering teams to share knowledge and best practices across the firm.
• Design and develop a cloud native high performance quantitative research platform.
• Design systems for distributed model fitting and signal generation on the research platform.
• Design and build tools for distributed backtesting of algorithmic trading strategies.
• Build out pipelines and tools for ingesting new datasets onto the research platform.
• Develop sophisticated data quality metrics and reporting to ensure mission critical datasets are consistent and reliable.
• Design and implement metadata tools such as data catalogs, feature stores, and signal catalogs.
• Create, monitor, and maintain production data pipelines required for daily trading activity.
• Strong problem solving skills with the ability to both turn around ideas quickly and work on longer term ambiguous projects.
• 2+ years of professional Python programming experience.
• Experience with the Python scientific computing stack (numpy, pandas, etc.).
• Excellent written and verbal communication skills for coordinating across teams.
• Experience with the following is a plus: