Senior Quantitative Data Analyst

Cedar Cares, Inc; Chicago (IL); On-site; USD 116,875 - 151,250; Full time

Benefits offered by this job

Competitive salary packages

Generous paid time off

Health, dental and vision benefits

401(k) match

Employee Stock Purchase Plan

Paid tuition assistance

Job summary

Cedar Cares, Inc is looking for a Senior Quantitative Analyst in Chicago, IL. This role involves analyzing datasets across equities, FX, options, and futures to transform complex market data into client-ready products. Ideal candidates should have a strong background in quantitative finance and data analytics.

Responsibilities include conducting market analysis and developing data products for institutional clients, while also applying statistical methods and advanced analytics.

The company offers a competitive salary and comprehensive benefits.

Qualifications

• 5-8+ years of experience in a quantitative data science or market data role.
• Strong understanding of cloud-based data platforms.
• Experience with statistical and machine learning techniques.

Responsibilities

• Analyze market microstructure across various trading instruments.
• Package datasets for institutional clients with usability focus.
• Apply statistical methods to improve dataset quality.

Skills

Quantitative analysis

Statistical modeling

Data analysis

Machine learning

Programming in Python

SQL

Education

Bachelor's or Master’s degree in Quantitative Finance, Data Science, or related field

Tools

Data visualization tools

Market data APIs

AWS

Snowflake

Job description

Role Overview

We are seeking a Senior 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.

Required Qualifications & Skills

• Education & Experience: Bachelor’s or Master’s degree in Quantitative Finance, Computer Science, Data Science, Statistics, Engineering, or a related field.
• 5-8+ 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, 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.

Benefits and Perks

• 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.
• 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.
• Paid Time Off.

Equal Employment Opportunity

We’re proud to be an equal opportunity employer and do not discriminate against any employee or applicant for employment based on any legally protected characteristic, including race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status. We are committed to fostering a workplace where all individuals are valued and respected.

Visa Sponsorship

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 (US only)

The anticipated base salary range for this role is $116,875 - $151,250, 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.