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Urgent! Lead Quantitative Analyst Job Opening In New York – Now Hiring Cboe Global Markets, Inc.

Lead Quantitative Analyst



Job description

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! 

Location: Chicago or NYC office (flex hybrid)

Overview:

We are seeking a Lead Quantitative Analyst with a strong product development mindset to analyze global real-time option models, applied to underlying equities and futures with dependencies on interest rate curves and FX. This role focuses on Research and Development, and Prototyping in new variations of our derivatives pricing models.

The ideal candidate will have expertise in quantitative finance, data analytics, and machine learning, with a track record of modeling the application of financial models to market data.

Key Responsibilities:

1.

Option Model Analysis & Research

  • Analyze existing implementations of option pricing models and conduct empirical research into the efficacy over options of different geographies and liquidity levels.
  • Apply statistical methods including classification models, regressions, and machine learning to identify features of derivatives that are most suited for each type of model.
  • Collaborate with engineering teams to ensure effective and consistent quality in analytic pipelines.
  • 2.

    Advanced Data Analytics & Machine Learning

  • Apply machine learning techniques to detect patterns, anomalies, in applying Model Fitted Theoretical pricing to different categories of options.
  • Utilize statistical modeling, regression analysis, and classification methods to improve calibration of Model Fitting methods.
  • Implement feature engineering approaches to improve the quality of production applications of real-time Model Fitting that use approaches such as SABR, Mixture Models, or SVI.
  • 3.

    Data Distribution & Market Engagement

  • Collaborate with hedge funds, asset managers, and proprietary trading firms to understand their options analytics needs and commercial use cases.
  • Assist sales and marketing teams in positioning and selling analytic data services to institutional clients.
  • Required Qualifications & Skills:

    Education & Experience

  • Master’s or PhD degree in Quantitative Finance, Computer Science, Data Science, Statistics, Engineering, or a related field.
  • 6 years of experience with a Master’s degree or 3 years with a PhD in a quantitative, data science, or research role  at a financial institution such as a bank, fund manager, market maker, or a risk analytics vendor.
  • Technical & Analytical Skills

  • Strong programming skills in Python (pandas, NumPy, scikit-learn) and SQL.

    Experience with R is a plus.
  • Experience with Java.

    Strong Java skills are a plus.
  • Experience with time-series analysis, and scalable computing.
  • Familiarity with machine learning techniques (supervised/unsupervised learning, feature selection, anomaly detection) that can include regression and decision tree methods such as Random Forest.
  • Finance & Trading Knowledge

  • Knowledge of quantitative finance models, and risk modeling.
  • Experience working with historical datasets for trading, backtesting, and risk management.
  • Familiarity with options and futures market structure, volatility analysis, and pricing models.
  • Product Development & Commercialization

  • Strong ability to translate quantitative findings into actionable production engineering results in collaboration with the Cboe Development Teams.
  • Strong ability to work with sales, marketing, and business development teams
  • Preferred Qualifications:

  • Ability to apply machine learning in finance, with use cases that could include
  • Benefits and Perks

    We value the total wellbeing of our people – including health, financial, personal and social wellness.

    We believe standard benefits like health insurance and fair pay are given at any organization.

    Still, you should know we offer:

  • Fair and competitive salary and incentive compensation packages with an upside for overachievement

  • Generous paid time off, including vacation, personal days, sickdays and annual community servicedays

  • 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% matchimmediately 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

  • Some of our associates’ favorite benefits and perks include:

  • 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


  • Required Skill Profession

    Mathematical Science Occupations



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