Lead Quantitative Analyst

Job Description:

Building trusted markets —powered by our people. 

At Cboe, 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 inclusive 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. Our Associate Resource Groups champion diversity, equity and inclusion, giving associates a safe space to network, share ideas and create opportunities.  

Sound like the place for you? Join us! 

Overview:

We are seeking a Quantitative Analyst with a strong product development mindset to analyze exchange data sets across multiple asset classes, specifically equities, FX, options, and futures. This role focuses on identifying and curating actionable datasets for commercial sale. The ideal candidate will have expertise in quantitative finance, data analytics, and machine learning, with a track record of designing and structuring historical datasets for institutional clients.

Location: NYC (flex hybrid)

Key Responsibilities:

1. Exchange Data Analysis & Research

• Analyze market microstructure across equities, FX, options, and futures to extract valuable insights.
• Evaluate raw exchange and proprietary datasets, identifying patterns that enhance trading, risk management, and execution strategies.
• Develop liquidity metrics, order book analytics, and price impact models to assess market behavior.

2. Data Product Development & Commercialization

• Design and package historical datasets for institutional clients, optimizing for usability, scalability, and monetization.
• Define product specifications, licensing models, and delivery mechanisms, including distribution channels such as Snowflake and AWS Marketplace.
• Ensure datasets are structured to support quantitative research, execution strategies, and regulatory compliance.
• Collaborate with engineering teams to ensure efficient data ingestion, normalization, and delivery pipelines.
• Stay ahead of market data trends, ensuring products remain competitive and innovative.

3. Advanced Data Analytics & Machine Learning

• Apply machine learning techniques to detect market patterns, anomalies, and predictive signals.
• Utilize statistical modeling, regression analysis, and clustering algorithms to enhance dataset value.
• Implement feature engineering and deep learning approaches to improve the quality and relevance of data products.

4. Data Distribution & Market Engagement

• Collaborate with hedge funds, asset managers, and proprietary trading firms to understand their data needs and commercial use cases.
• Conduct competitive analysis of alternative data providers and market data solutions.
• Assist sales and marketing teams in positioning and selling data products to institutional clients.

Required Qualifications & Skills:

Education & Experience

• Bachelor’s or Master’s degree in Quantitative Finance, Computer Science, Data Science, Statistics, Engineering, or a related field.
• 3-7 years of experience in a quantitative, data science, or research role at a trading firm, fintech, exchange, or data vendor.

Technical & Analytical Skills

• Strong programming skills in Python (pandas, NumPy, scikit-learn), SQL, and data visualization tools.
• Experience with big data processing, time-series analysis, and high-performance computing.
• Familia