Data Scientist | Post Trade Analytics

Jump Trading Group is committed to world-class research. We empower exceptional talent 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 fostering 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 complex problems. Jump Trading's Post-Trade Analytics (PTA) Team is the firm's central source of truth for understanding how we trade. We measure, analyze, and optimize every dimension of our trading activity across all global markets. Our team builds the foundational analyses that traders and quantitative researchers rely on daily to make critical decisions. Operating across highly diverse datasets, our core infrastructure collects, organizes, and stores billions of data points every day, powering the analytics behind a wide array of trading strategies. The primary role of the PTA team Data Scientist is to undertake cutting edge analysis on this data to uncover competitive edges. The role offers the opportunity to develop both business and technical expertise, while significantly contributing to Jump's business through the mining and enrichment of data. What You'll Do: Identify relationships between business metrics and changes on the infrastructure technology Partner with trading teams to perform post trade statistical analysis on trading performance Conduct research for the purpose of modeling exchange performance Develop mathematical methodology to quantify the impact that specific internal applications have on general performance Design innovative anomaly detection algorithms to detect performance degradation Develop and improve quantitative research frameworks using Python, C++, and other software systems Other duties as assigned or needed Skills You’ll Need: The ideal candidate will have the ability to work closely with and collaborate across trading and trading infrastructure teams. We are looking for an individual who is instinctively curious, self-driven, keen to dive into the complex world of HFT, and has demonstrated an ability to independently drive tasks and projects to completion in a team environment At least 3+ years of programming experience in Python with a data science and analytics focus Strong data intuition combined with a healthy skepticism for easy conclusions Excellent problem solving abilities Experience in documenting and communicating analysis to both technical and business audiences. Background in statistics Experience with C++ is a plus. Experience with SQL is a plus. Practical experience with Machine Learning technics is a plus. Understanding of network protocols (IP, UDP, TCP, Ethernet) is a plus. Reliable and predictable availability