Data Scientist - AI/ML & Enterprise Analytics

CFTC Orders United States Commodity Funds LLC; Washington (District of Columbia); Remote; USD 152,000 - 224,000; Full time

Job summary

Commodity Futures Trading Commission is seeking a Data Scientist to support the Division of Data in advancing data strategies, AI/ML analytics, and enterprise analytics across market segments. You will work with senior leaders to drive data-driven decisions and improve surveillance capabilities.

The role emphasizes data collection, cleaning, EDA, and building predictive models to strengthen analytics and risk assessment across agency programs.

Responsibilities

• Assist senior Data Scientists and support the CDS and CDO in developing, defining, and driving the CFTC's data strategy to advance AI, ML, and enterprise analytics across traditional and emerging market segments.
• Assist in identifying and developing data-driven solutions for complex business challenges to expand the agency's data analytics capabilities.
• Collect, clean, and analyze large datasets from multiple sources for data quality, accuracy, and integrity.
• Conduct exploratory data analysis on large, complex datasets to identify novel trends, patterns, relationships, and anomalies.
• Utilize modern tools and computational skills to interpret, connect, predict and make discoveries in complex data and deliver recommendations for business and analytic decisions.
• Develop predictive models that use advanced statistical and machine learning methods to strengthen the CFTC's surveillance capabilities and achieve policy goals.
• Assist in the development of AI and ML models for risk scoring and predictive measures to identify candidates for further investigation using structured and unstructured data.

Job description

Commodity Futures Trading Commission is seeking a Data Scientist to support the Division of Data in advancing data strategies, AI/ML analytics, and enterprise analytics across market segments. You will work with senior leaders to drive data-driven decisions and improve surveillance capabilities.

The role emphasizes data collection, cleaning, EDA, and building predictive models to strengthen analytics and risk assessment across agency programs.