Jump Trading

Jump Trading

Research Scientist/Research Engineer

Chicago, New York, London

Sponsorship not specified$200k-$350kDetected 106 days ago
PythonC++Machine LearningDeep LearningStatisticsResearchCommunicationCollaboration

About the role

  • We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets.

Responsibilities

  • The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure.

Requirements

  • 5+ years of experience in developing DL systems with measurable impact in industry and/or academia

Skills

  • Jump Trading Group is committed to world class research.
  • Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak.
  • Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
  • Proficiency in Python and/or C++
  • Strong foundation in mathematics and statistics
  • Ability to thrive in a collaborative, team-oriented environment
  • PhD, or Master's degree in Computer Science, Mathematics, (or related subject)
  • Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent
  • Reliable and predictable availability
  • Excellent written and verbal communication skills in English

Compensation

  • Annual Base Salary Range
  • $200,000 - $350,000 USD

Benefits

  • Discretionary bonus eligibility
  • Medical, dental, and vision insurance
  • HSA, FSA, and Dependent Care options
  • Paid vacation plus paid holidays
  • Retirement plan with employer match
  • Paid parental leave
  • Wellness Programs
  • We are seeking research scientists with a demonstrated ability to apply deep learning to achieve state-of-the-art capabilities in complex and challenging domains.

This listing is sourced directly from Jump Trading's careers page and normalized into a canonical job model.