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Quantitative Analyst, European CLB

Balyasny Asset Management · Hedge fund · London · Mid-level · Posted 2026-05-20

Apply now → Applications go to Balyasny Asset Management's own site.

Quantitative Analyst, European CLB

The Quantitative Analyst, European CLB will play a key role in supporting trading, development and research of the EMEA Central Liquidity Book.

This position is focused on intraday monitoring and management of CLB inventory, and medium-term projects to enhance the platform.

The ideal candidate will work closely with the global CLB team, the European trading desk, technology, compliance, and operations/support teams.

Responsibilities:

Tooling, Monitoring, & Automation

  • Drive automation of existing manual processes, working with team members to identify opportunities and implement solutions that enhance efficiency and control.
  • Support day-to-day trade monitoring activities, ensuring timely identification and resolution of issues, escalating as needed.

Execution Oversight

  • Partner with portfolio managers and senior team members to understand trading workflows and assist in optimizing order execution and liquidity provision.
  • Help maximize CLB usage by building out new features or functionalities
  • Ensure alignment with regulatory expectations and internal compliance standards.

Teamwork & Culture

  • Serve as an integral member of the CLB/Trading teams, contributing to a culture of accountability, transparency, and continuous improvement.
  • Participate in knowledge sharing, and process documentation to support team growth and operational excellence.

Requirements:

  • Possess an understanding of market impact, risk models, and alpha signals and how to balance the three using an optimizer
  • Have experience on pricing, hedging and managing risk
  • Familiarity with the European trading landscape, market structure, liquidity
  • Knowledge of execution algorithms
  • Bachelor’s degree in a quantitative or related field.
  • 3+ years of experience in trading related roles within financial services
  • Strong analytical, problem-solving, and communication ability
  • Proficiency in Python, KDB, SQL
  • Experience using AI to automate processes

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