The candidate will join the FX & DA Trading department, which serves the bank’s electronic trading business acting as principal counterparty in OTC venues and CLOBs, and particularly the SPOT liquidity team. 

As a team we:

• contribute to the bank’s commercial goals by managing our proprietary pricing, execution, and internalization systems
• provision competitive Spot liquidity while meeting internal risk policies
• ensure a gainful network of trading counterparties
• drive the bank’s ongoing investments in systematic capacities, in collaboration with software engineers and IT
• drive the quantitative research initiatives relevant to its business scope
• facilitate new business initiatives in collaboration with various internal teams
• ensure excellent service quality and engage in its continuous improvement

You will  play a primary role in implementing the team’s quantitative research roadmap, but also contribute to the team’s day-to-day duties. In this context, you may interact with clients and collaborate with colleagues in other departments e.g. relationship managers, quant researchers and a consulting academics, software engineers and IT experts.

Moreover, the role includes ad hoc data exploration/visualization and reporting to address Traders’ needs.

• 3+ years trading experience in a sell-side electronic trading firm/bank is a strong plus
• MSc/PhD in a STEM discipline from top ranked university
• Strong analytical and modelling skills suitable to financial tick-data
• Familiar with Machine Learning methods applied to financial predictions
• Strong in Python, especially with libraries relevant to large data-sets
• In-depth understanding of relevant market microstructure aspects such as:
  • the relationship between risk inventory, liquidity, spreads, volatility, credit, volumes
  • the resulting economics between liquidity providers and consumers
• Able to multi-task under pressure while maintaining focus on accuracy
• Available to deliver on time
• Self-driven, structured, attention to detail, team-oriented
• Excellent communication skills and able to develop relationships with interdisciplinary people
• Fluent in English