Advisory Seasonal Intern, Federal Technology Enablement - PhD Data Science​/Data Engineer | Winter

Position: Advisory Seasonal Intern, Federal Technology Enablement - PhD Data Science/Data Engineer | Winter 2027
Career Level Requirement  Early Career
If you are currently pursuing college coursework or have completed a bachelor’s degree or higher in the past 12 months. If it has been more than 12 months since you have graduated from an undergraduate or graduate degree program you should explore experienced career opportunities at KPMG Careers:
Experienced Professionals.
You are limited to a maximum of two active applications. Earliest Graduation Date:  May 2026
Latest Graduation Date:  Sep 2031
Harnessing the full power of AI and digital innovation, we deliver intelligent, data-driven solutions to help our clients navigate change and transform their competitive edge. KPMG invests in continuous learning by providing the tools and training for you to thrive within a culture that fosters growth and collaboration, whether you're launching your career or bringing decades of experience. KPMG is currently seeking an Advisory Seasonal Intern, Federal Technology Enablement - PhD Data Science/Data Engineer for our Advisory practice.

Conduct research and develop AI-powered capabilities—including anomaly detection models and agentic AI architectures—to solve real-world problems, identify systemic patterns and decompose complex queries into sub-tasks
Develop reproducible data pipelines to prepare and enrich data and design large-scale multi-relational knowledge graphs to engineer and evaluate complex graph-structured features
Research and implement post-hoc explainability methods that produce clear rationales for flagged entities, supporting iterative human-in-the-loop refinement for AI models
Iterate rapidly on models and experimental designs in a fast-paced research environment, while rigorously documenting assumptions and actively managing project risks
Partner with diverse teams—including data scientists, engineers, policy staff and federal client stakeholders—to translate advanced research outcomes into actionable program integrity recommendations
PhD program in Data Science, Computer Science, Electrical/Computer Engineering, or equivalent program
Government Security clearance
demonstrated ability to excel and drive strategic outcomes, coupled with a professional demeanor and a collaborative leadership approach, in a dynamic, evolving environment; understanding of statistical analysis and machine learning fundamentals; solid foundation in advanced graph or time series techniques preferred
Strong proficiency in SQL, Python and relevant open-source machine learning and data science libraries
Exposure to agentic AI frameworks (e.g., Lang Chain, Lang Graph, Auto Gen, or similar tool-using agent systems) and familiarity with data visualization tools (Tableau, Power BI) or open-source frameworks (Dash, Plotly, Shiny); experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) preferred
Must reside within a commutable distance of the office for this position and be responsible for your own transportation, such as personal vehicle or public transportation, to get to and from office / client locations to satisfactorily fulfill your job duties, as determined by your practice leadership; work location may be in the office, at client sites, or virtual/remote depending on business need;

S. when working remotely; client site locations may require travel and overnight/extended stay
S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual…