Leadership Rotation Network Analyst at DRW | GB | Rezi

Leadership Rotation Network Analyst at DRW

Leadership Rotation Network Analyst

DRW · GB

3 weeks ago

Leadership Rotation Network Analyst

DRW · GB

23 days ago
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About the Role

This yearlong middle and back-office rotation program, the Leadership Rotation Network (LRN), begins with an immersive onboarding experience to reinforce market fundamentals. It provides an opportunity to build relationships with cohort members and integrate into the LRN community. Following onboarding, participants will rotate through up to three targeted middle and/or back-office teams. Upon successful completion, participants will earn a post-LRN role aligned with career aspirations and DRW's business needs. This position is not a trading or quant role.

Responsibilities

  • Apply acquired knowledge and skills to deliver tangible value through rotations in various middle and back-office teams.
  • Analyze situations, develop solutions aligned with strategic goals, and respond constructively to feedback.
  • Collaborate effectively within diverse teams and build lasting relationships with cohort members and the LRN community.
  • Lead projects and participate in daily processes, gaining insight into each team’s scope and their collective role in supporting the trading business.
  • Develop a comprehensive understanding of the business and a foundation of how trading functions work together cohesively.

Requirements

  • A Bachelor’s or Master’s degree in Business, Finance, Business Analytics, Economics, or a related field, with a graduation date between December 2026 and June 2027.
  • A strong desire to learn, a curious mindset, a commitment to integrity, and the ability to deliver results both independently and as part of a team.
  • Excellent critical thinking and problem-solving skills, with the ability to learn quickly, act with urgency, and communicate effectively.
  • The ability to work independently while building strong relationships across business groups.
  • Strong Excel skills and comfort working with large, structured data sets.
  • Foundational knowledge of SQL, Python, or similar data tools, with the interest and ability to deepen these skills on the job.
  • The ability to use AI-enabled tools to accelerate analysis, troubleshoot issues, draft queries or scripts, summarize information, and identify opportunities to improve workflows.
  • Sound judgment when validating AI-generated outputs, protecting confidential information, documenting assumptions, and escalating uncertainty.
  • A demonstrated analytical mindset, strong attention to detail, and the ability to investigate data discrepancies, reconcile information across systems, and communicate conclusions clearly.
  • An interest in automation, process improvement, and using technology to reduce manual effort and operational risk.
  • Work authorization in the United Kingdom without the need for sponsorship in the future.

Skills

  • Excel
  • SQL
  • Python
  • AI-enabled tools
  • Analytical mindset
  • Attention to detail
  • Critical thinking
  • Problem-solving
  • Communication

Location

  • London

Work Type

  • Onsite
  • Full-time

Experience Level

  • New graduate

Education Level

  • Bachelor's degree
  • Master's degree

About the Company

  • DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world.
  • DRW operates using its own capital and trading at its own risk.
  • Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, DRW trades a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets.
  • DRW has leveraged its expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.
  • DRW operates with respect, curiosity and open minds.
  • DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.