Quantitative Data Analyst

Cboe Global Markets • Chicago, IL

10d • $88,825 - $114,950 • Hybrid

About The Position

Cboe Global Markets is seeking a quantitative analyst with a product development mindset to analyze exchange datasets across equities, FX, options, and futures and help turn complex market data into practical, client-ready products. The role focuses on identifying, structuring, and enhancing datasets for commercial use, supporting trading, risk, execution, quantitative research, and compliance needs.

The position involves exchange data research and analytics, historical data product development and commercialization, statistical and machine learning applications, data distribution and market engagement, product documentation, product operations, and quality assurance. The role partners with internal teams and clients, including Engineering, Technology, Operations, Support, and Sales, to develop, document, deliver, test, and support data products. It follows a four-day-in-office work model at Cboe's Chicago headquarters.

Candidates must be legally authorized to work in the United States without current or future employer visa sponsorship. The anticipated U.S. base salary range is $88,825–$114,950. The role may also be eligible for annual incentive compensation and, where applicable, participation in Cboe's long-term equity programs.

Requirements

• Bachelor’s or Master’s degree in Quantitative Finance, Computer Science, Data Science, Statistics, Engineering, or a related field.
• 2–5+ years of experience in a quantitative, data science, research, or market data role at a trading firm, exchange, fintech, or data provider.
• Programming skills in Python and SQL.
• Experience with data analysis and visualization tools.
• Familiarity with machine learning techniques such as supervised learning, clustering, and anomaly detection.
• Working knowledge of market data APIs, real-time data processing, or related infrastructure.
• Must be legally authorized to work in the United States without the need for employer sponsorship now or in the future.

Nice To Haves

• Exposure to cloud-based data platforms such as Snowflake, AWS, or GCP.
• Prior experience at a market data provider, exchange, or trading analytics firm.
• Familiarity with cloud-based data processing (AWS, GCP, Azure) and distributed computing frameworks.
• Ability to apply machine learning in finance, particularly in predictive modeling and trading signals.

Responsibilities

• Analyze market microstructure across equities, FX, options, and futures to identify actionable insights.
• Evaluate exchange and proprietary datasets for trading, risk, and execution use cases.
• Build liquidity metrics, order book analytics, and related measures to assess market behavior.
• Help design and package historical datasets for institutional clients, emphasizing usability and scale.
• Support product specifications and delivery approaches, including cloud distribution channels such as Snowflake and AWS Marketplace.
• Structure datasets for quantitative research, execution analysis, and compliance needs.
• Partner with engineering teams on data ingestion, normalization, and delivery workflows.
• Apply statistical and machine learning techniques to identify patterns, anomalies, and predictive signals.
• Use modeling, regression, and clustering methods to improve dataset quality and generate insights.
• Work with internal teams and clients to understand data needs and commercial use cases.
• Conduct competitive analysis of market data and alternative data offerings.
• Support Sales and Marketing with analytics and product positioning for client discussions.
• Draft and maintain product specifications, FAQs, release notes, and client-facing documentation.
• Track website content updates and verify consistency across products and channels.
• Assist with change notifications, product announcements, and related communications.
• Manage action items across Product, Technology, Operations, Support, and Sales.
• Maintain product support materials and track key product dependencies.
• Assist with onboarding new products and coordinating releases.
• Coordinate issue investigations and follow-up activities with internal teams.
• Validate sample files, schemas, field mappings, and related documentation.
• Support product testing, website releases, and launch activities.
• Verify production outputs following launches and enhancements.

Benefits

• The role may be eligible for annual incentive compensation.
• Where applicable, participation in Cboe's long-term equity programs.
• Cboe describes a total rewards program that includes benefits and other compensation components, but specific benefits are not listed.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level