Intercontinental Exchange - New York, NY

posted 3 months ago

Full-time - Senior
New York, NY
Securities, Commodity Contracts, and Other Financial Investments and Related Activities

About the position

The Director, Artificial Intelligence/Machine Learning is a pivotal role within a newly established and highly visible team at NYSE, integral to the organization's long-term strategy aimed at enhancing the analysis of market microstructure data. This position is designed to deepen the understanding of market behavior and to provide customers with value-added data sets. The team is currently small but is envisioned to expand into a larger business unit as it grows in capability and scope. The ideal candidate for this role is expected to be a self-starter who is hands-on and ready to build the department from the ground up. This individual will work independently and collaboratively to research, design, develop, and implement innovative solutions in Machine Learning, Artificial Intelligence, deep learning, Natural Language Processing (NLP), Cloud computing, and Data Science. These solutions will significantly advance NYSE's analytics capabilities across various business lines, ensuring that the organization remains at the forefront of technological advancements in the financial sector. In this role, the Director will be responsible for brainstorming and identifying innovative applications of ML/AI/NLP in quantitative analysis and surveillance, which will facilitate automation, knowledge discovery, decision-making, and insights. The position requires a blend of technical expertise and the ability to communicate complex models and algorithms to both technical and non-technical stakeholders. The Director will also be tasked with evaluating trade-offs between internal implementations and potential partnerships with external teams or vendors to leverage new technology-based solutions. Regular engagement with management and staff will be essential to provide updates on project statuses and to discuss relevant issues, ensuring alignment with the organization's strategic goals.

Responsibilities

  • Brainstorm identifying ML/AI/NLP innovations to apply in quantitative analysis on market microstructure and in surveillance to help in advance automation, knowledge discovery, decision-making and insights
  • Implement and prototype new algorithms and write code for novel ML/AI/NLP solutions
  • Experiment and evaluate various solutions through prototyping, POCs and quantitative metrics, and handing off solutions to stakeholder teams as needed
  • Explain complex models to stakeholders and managers in simple terminology, while also being able to discuss intricacies of complex algorithms with experts in the field
  • Figure out tradeoffs between internal technical implementation vs. partnerships with external teams/organizations/vendors for new technology-based solutions and capabilities
  • Research emerging ML/AI/NLP and other Data Science solutions to be conversant with latest developments in these fields
  • Attend and present at technical conferences, workshops, and meetups
  • Regularly meet with the management and staff to deliver presentations, project status, and discuss relevant project issues
  • Conduct and document status meetings and project reviews
  • Supervise assigned staff in the day-to-day development of applications and production support
  • Provide feedback and input into the development of system design and implementation plans
  • Keep management updated on progress and on-going production issues

Requirements

  • Bachelor's degree in Computer Science, Engineering or similar discipline
  • 10 or more years of experience in multiple technology disciplines with extensive experience in business, functional and people management
  • 5 or more years of experience in financial domain
  • 2 or more years of experience in applying AI/ML/NLP/deep learning/data-driven statistical analysis & modelling solutions to quantitative analysis to financial market data
  • Strong Knowledge of the theory and applications of machine learning, AI, deep learning, data science, NLP, text analytics, unstructured data analytics, supervised/unsupervised learning
  • Strong, proven programming skills in Python, C/C++, Java, R, MATLAB, Scala, and with machine learning and deep learning and Big data frameworks including TensorFlow, Caffe, Spark, Hadoop
  • Experience with writing complex programs and implementing custom algorithms in these and other environments
  • Experience beyond using open source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworks
  • Proven capability in demonstrating successful advanced technology solutions (either prototypes, POCs, well-cited research publications, and/or products) using ML/AI/NLP/data science in one or more domains
  • Experience in data management, data analytics middleware, platforms and infrastructure, cloud and fog computing is a plus
  • Experience in data visualization solutions and data visualization tools is a plus
  • Additional experience with GPU programming for training deep learning models, and cloud environments such as AWS is desirable
  • Excellent communication skills to explain complex algorithms, solutions to stakeholders across multiple disciplines, and ability to work in a diverse team
  • Experience in an applied R&D environment, working in an agile, innovation-lab culture to bring cutting-edge technologies to fruition, from initial concept to implementation

Nice-to-haves

  • Experience in data visualization solutions and data visualization tools is a plus
  • Additional experience with GPU programming for training deep learning models, and cloud environments such as AWS is desirable
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