Jump Trading Group is committed to world class research. 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. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis, machine learning and deep learning skills, using the results of their research to make forecasts and develop profitable predictive trading models.
What You’ll Do:
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. 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. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.
Skills You’ll Need:
- At least 5+ years of experience in developing DL systems with measurable impact in industry and/or academia.
- 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.