Data Scientist | Post Trade Analytics

Jump Trading Jump Trading · Quant · Shanghai, China · Core Development

Data Scientist role focused on post-trade analytics in financial markets, involving analysis of trading performance, PnL metrics, latency, and infrastructure. The role requires developing mathematical methodologies, designing alert detection algorithms, building datasets, and improving quantitative research frameworks, with a strong emphasis on Python programming and statistical background.

What you'd actually do

  1. Partner with trading teams to perform post trade analysis on trading performance, linking PnL metrics with latency and other infrastructure measurements
  2. Identify relationships between business metrics and changes in the infrastructure technology
  3. Conduct research for the purpose of modeling exchange performance
  4. Develop mathematical methodology to quantify the impact that specific internal applications have on general performance
  5. Design innovative alert detection algorithms to proactively detect new business opportunities, performance degradation or abnormal PnL-impacting events

Skills

Required

  • Python programming with a data science and analytics focus
  • Strong data intuition
  • Excellent problem-solving abilities
  • Documenting and communicating analysis to both technical and business audiences
  • Background in statistics

Nice to have

  • SQL
  • Machine learning techniques
  • Understanding of network protocols (IP, UDP, TCP, Ethernet)