Quant Data Engineer

Nova Prospect is a systematic prop trading firm, founded by industry experts who previously built some of the most successful businesses in algorithmic trading and finance. This is a rare opportunity to join a growing A-team with incredible talent density, meritocratic culture, no politics and razor-sharp focus on outcome.

The ideal candidate is demonstrably among the best in their field, highly ambitious and a proven problem-solver with excellent judgement. Successful candidates will have the opportunity to learn from the best, grow their role significantly over time and build a highly rewarding, long-term career in systematic trading.

Responsibilities
. Architect, implement and operate a pipeline for ingesting crypto data from a wide range of different sources, covering both market data and alternative datasets
. Deliver high-quality, highly available, normalized data to our quant researchers and developers for research and production applications
. Build a scalable platform for data monitoring, quality assurance, and data cataloguing
. Closely collaborate with our quant researchers to identify opportunities to enhance our datasets and enable new research
. Apply data science and machine learning methods to create derived data and custom datasets, and to analyze our data
. Discover and source new datasets, and have a significant and quantifiable impact on our trading performance

Qualifications
. Master's degree or Ph.D. in Computer Science, Engineering, Physics, Applied Math, Statistics, or related discipline strong candidates with a Bachelor's degree will also be considered
. 1 to 2 years of experience in processing and transforming large datasets, and a passion for exploring and working with data
. Strong software design and development skills in Python, Java or other OOP language
. Familiarity with cloud environments and Linux
. Systematic, detail-oriented and meticulous approach to working with data
. Ability to work closely with quant researchers and quant developers in a highly collaborative environment
. Exposure to data science and machine learning methods is a plus
. Experience working for a financial firm or data vendor in a data engineering role is a strong plus but not required - we will invest in the right candidate