New York, New York, United States
2 months ago

Job Overview

Pay
Not disclosed

Job description

Location:
New York, New York, United States
Work arrangement:
On-site

Role Summary

About the position

We’re looking for a Data Strategist who can understand the external data landscape, identify datasets that could improve our trading, and procure that data.

You’ll partner closely with traders, researchers, and other colleagues to understand their work, advise them on what data could help, and compare their options. You’ll learn what data exists by attending conferences, following industry developments, meeting vendors, and investigating sources that may hold valuable data even if it isn't yet commercialized.

You’ll manage our vendor relationships to vet promising products, negotiate contract terms, and influence vendor roadmaps, while coordinating with our Legal, Compliance, Finance, and Data Engineering teams to bring datasets into production use.

About you

  • Professionally experienced with sourcing, evaluating, and procuring datasets
  • Analytical, curious, and quick to build expertise in new areas
  • Able to build strong relationships with colleagues across the firm and with outside vendors
  • Able to manage multiple concurrent projects and context-switch throughout the day
  • A strong written and verbal communicator

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

Role:
Data Strategist

Company profile

Jane Street

janestreet.com

Jane Street is a quantitative trading firm and liquidity provider that focuses on technology and collaborative problem solving. Established in 2000 by a small group of traders and technologists in a New York office, it now has more than 3000 employees across five global offices and trades a broad range of asset classes on more than 200 venues in 45 countries. Alongside its proprietary trading, Jane Street commits its capital, technology and expertise to help institutions meet their trading goals, and it works in areas from functional programming to machine learning.

Founded
2000

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