ICE · 2 days ago

Data Scientist

New York, NY

Full-time

Onsite

Senior Level

$195K/yr - $245K/yr

4+ years exp

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Responsibilities

Design models and perform analyses on large quantities of data to identify trends in market activity and potential violations of securities laws.

Use predictive modeling, machine learning, and advanced statistical methods to develop automated surveillances.

Research, develop, and design new surveillances to identify potential misconduct on the NYSE exchanges.

Build surveillance prototypes using CAT data.

Refine surveillance prototypes to address changing market conditions.

Monitor developments and trends associated with market structure and trading on the NYSE exchanges.

Work closely with NYSE Regulation staff to understand surveillance requirements and exchange rules.

Participate in periodic surveillance assessment reviews and implement enhancements.

Assist with user acceptance testing and support.

Represent NYSE Regulation in working groups and industry initiatives.

Qualification

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SQLPythonData-Structured LanguagesBig DataStatistical ModelingMachine LearningDeep LearningEquities TradingOptions TradingMarket StructureUS Securities LawsBusiness Needs UnderstandingProblem-SolvingCuriosity Work in Fast-Paced EnvironmentCollegialityTime ManagementTrade Surveillance Systems

Required

Bachelor’s degree in computer science, data science, finance or mathematics with a minimum of eight years of experience or a master’s degree with a minimum of four years of experience.

Strong knowledge of SQL, Python, data-structured languages, and big data.

Hands-on experience building statistical, machine learning, and deep learning models.

Previous experience with management of trade surveillance systems desirable.

Developed understanding of equities and options trading, market structure, and securities laws, regulations and rules highly desirable.

Intellectual curiosity and an ability to grasp broader needs of business and regulation stakeholders.

Ability to work in a fast-paced, demanding, and collegial environment while handling multiple projects at the same time.