Lead Data Analyst
Jump Trading is a global trading firm.
About Jump Trading
Jump Trading is a global trading firm focused on research-driven trading and the engineering of scalable models, tools, infrastructure, and execution systems. Its operations combine trading, technology, AI/ML, and quantitative research, and it also runs research and talent programs including conference travel grants and a fellowship program.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead the proprietary data team’s daily work, translating business requests into defined projects, setting priorities, and driving delivery. You will establish standards for data collection, tagging, documentation, and validation; review outputs; coach analysts; solve ambiguous data problems; communicate findings; and partner on automation with appropriate human review.
Requirements
- 7+ years of hands-on financial-industry data experience
- 3+ years of experience leading complex projects and other analysts
- Experience collecting, tagging, and cleaning data
- Familiarity with alternative, fundamental, market, and reference data
- Expertise in at least one asset class and its data and market conventions
- Proficiency in Python, SQL, and Excel
- Experience using LLMs, agents, and coding assistants for data work
- Written and verbal communication, analytical, and problem-solving skills
Responsibilities
- Coordinate the team’s work and translate requests into well-defined projects
- Set priorities across competing demands and drive projects to completion
- Set standards for data collection, tagging, documentation, and validation
- Review the team’s output before delivery to researchers and traders
- Assign work, provide feedback, and coach analysts on research techniques and AI tools
- Solve ambiguous and high-stakes data problems
- Serve as the primary point of contact and communicate findings, status, and expectations
- Partner with data engineers to automate manual workflows and maintain human review of automated pipelines