Sr Manager Machine Learning, Regulatory - Hybrid/Remote



Software Engineering, Legal
Multiple locations
Posted on Friday, April 5, 2024

Job Description

About Cboe

Cboe is one of the world’s largest exchange holding companies, offering cutting-edge trading and investment solutions to investors around the world.

What We Do

The regulatory technology team develops technology solutions to surveil 10 different equities, options and futures trading venues across US and Europe.

Our managers lead high performing engineering teams to deliver on mission critical projects to build and support market surveillance systems. We process data from 10 equities, options and futures market exchange platforms across the US, Europe, and are growing across other regions and market venues around the globe. We architect systems that can analyze billions of events per day. We optimize for increases in data volumes. We strive to create insights and data that provides actionable intelligence to our analysts to ensure fair, orderly and complaint operation of all our markets. We are analytical thinkers; we are humble and always striving to learn something new.

Location: Flex Hybrid in Lenexa, KS or Chicago, IL. Or can be remote with some travel.


The Sr Manager Machine Learning, Regulatory Technology will lead a team of ML engineers that support our market surveillance program. This is a unique opportunity to scale up a Machine Learning team and build an ML architecture to pave the way for applying Machine Learning in innovative ways to vast amounts of our data.

  • Come up with new machine learning concepts and experiments that are relevant to the market surveillance concepts being considered by the regulatory division.
  • Prototype the new ML concepts to set the path forward for ML engineers on the team to implement those.
  • Develop, advocate, and implement new technical architectures to shorten the cycle time between ML experimentation and production.
  • Organize and facilitate discussions with surveillance teams to whet new machine learning concepts, document approved ideas and follow through to implementation.
  • Build and promote the culture of clear communication, documentation, and transparency around new and on-going ML projects within regulatory division.
  • Inspire the engineers on the team to continuously expand their knowledge of latest developments in the Machine Learning, data Engineering and cloud computing space.
  • Plan ML projects and assign ML engineers to those based on priority and skillset.
  • Maintain up to date sprint plans, estimates, velocity charts for assigned projects and provide regular status updates to all stakeholders.
  • Manage stakeholder relationships, proactively look out for any execution related concerns, and address them.
  • Lead the recruitment efforts for ML engineers on the team.
  • Mentor direct reports to strive for high degree of individual and team level excellence, provide just in time constructive feedback.
  • Conduct performance planning and reviews as per organizational and departmental guidelines.
  • Participate in required regulatory compliance procedures and meetings and implement controls to ensure compliance by the development team.
  • Represent the technical needs of the ML team to gain support from other engineering teams and rest of the regulatory division.

Job Requirements

  • Minimum eight years of overall technology management experience leading small application development teams in an enterprise environment.
  • At least three years of hands-on experience training, tuning and productionizing machine learning models.
  • Proficiency in common machine learning frameworks, algorithms and libraries
  • Hands on experience using Python as primary programming language working with large datasets.
  • Hands on experience using SQL as an application developer and data analyst.
  • Hands-on development experience in AWS cloud using big data analytics and ML services such as Amazon SageMaker and Amazon EMR is highly desired, can be substituted with equivalent experience on other popular cloud environments.
  • Excellent communication skills and demonstrated experience in presenting to and getting buy in from enterprise audience.
  • Prior experience using agile methodologies and test-driven development is highly desired.
  • Exchange technology or market regulatory technology experience will be a huge plus.
  • Financial services industry experience will be a plus.
  • Bachelor’s degree in computer science, Mathematics, Statistics, Engineering, or a related field. A master’s or Ph.D. degree is preferred.




As required by the New York City Human Rights Law, Cboe provides a reasonable range of minimum base salary for roles that may be performed in New York City. Actual compensation is influenced by a wide array of factors including but not limited to geographic location, skill set, level of experience, etc. For New York City only, the range of starting base salary for this role is $200,000-$330,000. Additional incentive compensation and benefits may be available.

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.