Posted:
1/20/2026, 2:20:59 PM
Location(s):
Shanghai, China ⋅ Shanghai, Shanghai, China
Experience Level(s):
Mid Level
Field(s):
Data & Analytics
Pay:
$186/hr or $386,880 total comp
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.
Jump Trading's Post Trade Analytics Team plays a crucial role in measuring and optimizing performance and trade execution across all global markets where the firm operates. This team is responsible for developing, operating, and maintaining performance measurement solutions, as well as conducting a wide range of post-trade analyses for various departments, including trading, business development, and other central teams. Daily, the team's core infrastructure collects, organizes, and stores billions of data points related to trading performance.
This role offers the opportunity to develop both business and technical expertise while significantly contributing to our global post trade analytics effort. We are seeking an experienced Data Engineer with 3+ years of experience to work closely with our Shanghai team, building and maintaining sophisticated datasets and data pipelines that will shape the way we trade.
What you’ll do:
Skills you’ll need:
Website: https://www.jumptrading.com/
Headquarter Location: Chicago, Illinois, United States
Employee Count: 251-500
Year Founded: 1999
IPO Status: Private