Leadership Rotation Network Analyst
DRW is a Chicago-based diversified trading firm that uses technology, quantitative research, and risk management to provide liquidity across traditional and digital-asset markets.
About DRW
Founded by Don Wilson in 1992, DRW trades for its own account across global markets and operates strategies in cryptoassets, venture capital, real estate, carbon markets, and public-equity investments. Its crypto business, Cumberland, has provided institutional crypto-asset liquidity since 2014.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Participate in DRW’s yearlong Leadership Rotation Network, completing onboarding and rotating through up to three middle- and back-office teams. Analyze situations, develop solutions, lead projects, investigate discrepancies, reconcile information, and communicate conclusions while building knowledge of trading operations.
Requirements
- Bachelor's or Master's degree in Business, Finance, Business Analytics, Economics, or a related field
- Graduation between December 2026 and June 2027
- Critical thinking and problem-solving skills
- Strong Excel skills
- Foundational knowledge of SQL, Python, or similar data tools
- Ability to use AI-enabled tools for analysis and workflow improvement
- Ability to validate AI-generated outputs and protect confidential information
- Analytical mindset and attention to detail
- Interest in automation and process improvement
- Work authorization in the United Kingdom without future sponsorship
- Interest in trading and technology
- Understanding of financial securities and their markets
- Prior internship experience in or exposure to middle- or back-office roles
Responsibilities
- Apply knowledge and skills during middle- and back-office rotations
- Analyze situations and develop solutions
- Respond constructively to feedback
- Collaborate across diverse teams
- Lead projects and participate in daily processes
- Investigate data discrepancies
- Reconcile information across systems
- Communicate conclusions clearly
