Lead Quantitative Analyst

About the position 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. Responsibilities • 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. • 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. • Utilize 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. • 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. Requirements • 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. • 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. • Familiarity with machine learning techniques (supervised/unsupervised learning, feature selection, anomaly detection). • Expertise in market data APIs, FIX protocol, and real-time data processing. • Hands-on experience with cloud-based data distribution, including Snowflake, AWS Marketplace, and GCP datasets. • Deep understanding of market microstructure, order book dynamics, trade execution, and transaction cost analysis (TCA). • Knowledge of quantitative finance models, portfolio optimization, and factor-based trading strategies. • Experience working with historical datasets for trading, backtesting, and risk management. • Familiarity with options and futures market structure, volatility analysis, and pricing models. • Strong ability to commercialize financial datasets, working with sales, marketing, and business development teams. • Strong ability to translate quantitative findings into actionable, revenue-generating data products. • Understanding of data licensing, compliance, and alternative data commercialization. Nice-to-haves • 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. Benefits • Fair and competitive salary and incentive compensation packages with an upside for overachievement. • Generous paid time off, including vacation, personal days, sick days and annual community service days. • Flexible, hybrid work environment. • Health, dental and vision benefits, including access to telemedicine and mental health services. • 2:1 401(k) match, up to 8% match immediately upon hire. • Discounted Employee Stock Purchase Plan. • Tax Savings Accounts for health, dependent and transportation. • Employee referral bonus program. • Volunteer opportunities to help you give back to your communities. • Complimentary lunch, snacks and coffee in any Cboe office. • Paid Tuition assistance and education opportunities. • Generous charitable giving company match. • Paid parental leave and fertility benefits. • On-site gyms and discounts to other fitness centers. Apply tot his job