VP/Data Scientist Public Equity Strategies

September 17, 2020
New York, NY
Job Type


The Public Equity Strategies Group oversees a portfolio of external hedge funds and develops proprietary absolute return strategies.  In addition, the group is developing capabilities for quantitative, factor-based evaluation of external managers and optimal capital allocation across external hedge funds, internal strategies, and long-only equities strategies. 

Your Contributions

The VP/ Data Scientist will:

  • Have strong interest in collection data
  • Work with fellow quant researchers and identify useful data sources
  • Source, clean, map, and store data into internal database for research and trading 

The VP / Data Scientist (senior role) will work closely with the Public Equities group’s quant group and the deep resources of COMPANY’s Investment Division (IT, the Science team, etc.) in the course of his or her work.  Over the horizon of 3 years, the Public Equity Strategies Group is expected to create a highly diversified, high performance portfolio with capacity in the billions of USDs.  The Data Scientist will be a strong contributor to the achievement of that goal.

What we are looking for

  • Ideal candidates will have two or more years of strong data scientist/quant experience. 
  • They will also demonstrate achievements in creative problem solving, a solid foundation in mathematics and statistics, solid programming skills.
  • Candidate selection will place emphasis on data related programming (AWS, web scraping for example) and practical experience with data management, as is the willingness to collaborate with other groups in COMPANY in technology and quantitative analysis fields. 

Specific skills and experience sought include:

  • Post-graduate degree in a hard science (physics, engineering, Math, statistics, etc.)
  • Lead development of point-in-time data load framework project in ETL alternative data for trading
  • Develop web scrapes to collect alternative data.
  • Onboard trading-critical and research-critical datasets
  • Map and clean data
  • Expertise in Python, Jenkins, Kafka, ZeroMQ, AWS (SQS, RDS, S3, ElasticSearch, Batch, Codebuild), Redis, CouchBase, Snowflake, Vertica, Kubernetes, Airflow, Docker, Spark, Django ORM, Linux/Unix
  • Work background in a hedge fund, asset management firm or a technology start-up would be ideal
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