Quantitative Researcher
Skills
About the Role
You will design and develop data methodologies that synthesize multiple sources into defensible market signals. You will develop a deep understanding of available datasets, their limitations, and optimal use cases. You will implement data signals with direct impact on revenue and institutional adoption. You will leverage advanced proficiency in Python, SQL, and statistical programming to move from exploratory analysis to production systems. You will demonstrate mastery in time-series analysis, pattern recognition, and large-scale data problems. You will apply expertise in asset pricing, liquidity measurement, and market data systems. You will serve as the subject matter expert representing quantitative products to institutional clients. You will translate sophisticated financial engineering concepts into clear, logical explanations for non-technical audiences. You will relay market feedback from institutional partners back to product and engineering teams.
Requirements
- 5+ years of professional experience in quantitative research, financial engineering, or related quantitative roles
- Expert-level proficiency in Python and SQL
- Deep, practical knowledge of market data systems, and reference data architecture
- Proven experience designing and deploying pricing methodologies for financial assets
- Experience with liquidity measurement, market impact analysis, or similar quantitative market microstructure work
- Strong grasp of how institutional clients evaluate and adopt new data infrastructure
- Demonstrated ability to solve non-trivial problems with minimal guidance
- Ability to communicate advanced quantitative concepts with clarity to audiences ranging from engineers to C-suite executives
- Background at quantitative trading firms, hedge funds, or proprietary trading desks
- Experience with decentralized finance (DeFi) or next-generation financial infrastructure
- Prior work at market data providers or exchanges
- Exposure to Index design and maintenance
Responsibilities
- Design and develop data methodologies that synthesize multiple sources into defensible market signals.
- Develop a deep understanding of available datasets, their limitations, and optimal use cases.
- Implement data signals with direct impact on revenue and institutional adoption.
- Leverage advanced proficiency in Python, SQL, and statistical programming to move from exploratory analysis to production systems.
- Demonstrate mastery in time-series analysis, pattern recognition, and large-scale data problems.
- Apply expertise in asset pricing, liquidity measurement, and market data systems.
- Serve as the subject matter expert representing quantitative products to institutional clients.
- Translate sophisticated financial engineering concepts into clear, logical explanations for non-technical audiences.
- Relay market feedback from institutional partners back to product and engineering teams.