Quantitative Data Analyst

Job Description

Building trusted markets — powered by our people

At Cboe Global Markets, we inspire our people to solve complex challenges together because what we do matters. We provide the financial infrastructure that powers the global economy. As a leading provider of market infrastructure and tradable products, Cboe delivers cutting-edge trading, clearing and investment solutions to market participants around the world.

We’re building meaningful ways to support professional and personal development while strengthening the trust we’ve earned as a global market leader. Our teams are empowered to share ideas, actively pursue them and bring on a challenge. As champions of internal mobility and access to opportunity, we encourage our people to “go for it” and equip our managers with the training to coach their teams to the next level. We strive to provide employees a safe space to network, share ideas and create opportunities.

PLEASE NOTE: To support strong partnership and team connection, this role follows a four day in office work model.

Location Overview

Cboe HQ is located in the historic Old Post Office district, it’s a landmark that blends classic architecture with modern amenities. The building features expansive spaces with high ceilings and large windows, offering an abundance of natural light and panoramic views of the city skyline and the Chicago River.

With its prime location in the heart of downtown, the OPO Building provides easy access to major transportation hubs, including Union Station and multiple CTA lines, making it convenient for commuters. The building is home to a variety of amenities, including restaurants, a fitness center, and collaborative workspaces, creating a vibrant and dynamic work environment in one of Chicago's most iconic areas.

Role Overview

We are seeking a Quantitative Analyst with a strong product development mindset to analyze exchange datasets across equities, FX, options, and futures. This role focuses on identifying, structuring, and enhancing datasets for commercial use. The ideal candidate brings experience in quantitative finance, data analytics, and statistical modeling, with the ability to turn complex market data into practical client-ready products.

Key Responsibilities

1. Exchange Data Analysis & Research

• Analyze market microstructure across equities, FX, options, and futures to identify actionable insights.

• Evaluate exchange and proprietary datasets to support trading, risk, and execution use cases.

• Build liquidity metrics, order book analytics, and related measures to assess market behavior.

2. Data Product Development & Commercialization

• Help design and package historical datasets for institutional clients with a focus on usability and scale.

• Support product specifications and delivery approaches, including cloud distribution channels such as Snowflake and AWS Marketplace.

• Ensure datasets are structured for quantitative research, execution analysis, and compliance needs.

• Partner with engineering teams on data ingestion, normalization, and delivery workflows.

3. Advanced Data Analytics & Machine Learning

• Apply statistical and machine learning techniques to identify patterns, anomalies, and predictive signals.

• Use modeling, regression, and clustering methods to improve dataset quality and insight generation.

4. Data Distribution & Market Engagement

• 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.

5. Product Documentation & Communication

• 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.

6. Product Operations & Coordination

• 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.

7. Product Support & Quality Assurance

• Coordinate issue investigation 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.

Required Qualifications & Skills:

Education & Experience

• 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.

Technical & Analytical Skills

Programming skills in Python and SQL, with experience in 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.

Exposure to cloud-based data platforms such as Snowflake, AWS, or GCP is a plus.

Preferred Qualifications

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.

This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the United States without the need for employer sponsorship now or in the future.

Salary Ranges (applicable for US locations only)

At Cboe, we are committed to providing a competitive, transparent, and market‑informed total rewards program. The anticipated base salary range for this role is $88,825-$114,950, with actual compensation determined by job‑related factors such as skills, relevant experience, education, internal alignment, and location.

This role may also be eligible for annual incentive compensation and, where applicable, participation in Cboe's long-term equity programs.

Additional information about Cboe's total rewards program, including benefits and other compensation components, can be found here: Total Rewards at CBOE.

Any communication from Cboe regarding this position will only come from a Cboe recruiter who has a @cboe.com email or via LinkedIn Recruiter. Cboe does not use any other third party communication tools for recruiting purposes.