Quantitative Post-Trade Analytics Scientist

Jump Trading; Hong Kong; On-site; HKD 1,000,000 - 1,800,000; Full time

Job summary

Jump Trading Group, a leading quantitative research firm, is seeking a high-caliber quantitative professional to help analyze and optimize trading activities across global markets. The role focuses on post-trade analytics, performance modeling, and anomaly detection within a collaborative PTA team.

The candidate will develop methods using Python, C++, and related systems, partnering with trading teams to drive data-driven decisions and advance research capabilities in a fast-paced, innovative

Qualifications

• 3+ years of programming experience in Python with a data science focus.
• Strong data intuition and skepticism for easy conclusions.
• Excellent problem solving abilities.
• Experience in documenting and communicating analysis to both technical and business audiences.
• Background in statistics.
• Practical experience with Machine Learning techniques.
• Understanding of network protocols (IP, UDP, TCP, Ethernet) is a plus.
• Reliable and predictable availability.

Responsibilities

• 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

Data science

Statistics

Machine Learning

Problem solving

Documentation

Data intuition

Networking protocols

Tools

Python

C++

SQL

Job description

Jump Trading Group, a leading quantitative research firm, is seeking a high-caliber quantitative professional to help analyze and optimize trading activities across global markets. The role focuses on post-trade analytics, performance modeling, and anomaly detection within a collaborative PTA team.

The candidate will develop methods using Python, C++, and related systems, partnering with trading teams to drive data-driven decisions and advance research capabilities in a fast-paced, innovative