Summer 2027 AI/ML Modeler Intern
F.N.B. CorporationAbout the role
Primary Office Location
626 Washington Place. Pittsburgh, Pennsylvania. 15219. Join our team. Make a difference - for us and for your future. Deadline to submit application: October 17. 2026 Paid Internship No Corporate housing is offered and/or available FNB will not provide sponsorship for employment-based visas for this position; only candidates who are legally authorized to work in the U.S. will be considered.
Internship Overview / Summary
This role requires a highly motivated and detail-oriented AI/ML Modeler & Developer to join FNB enterprise data engineering and architecture technology team. This internship is ideal for a rising college junior passionate about applying machine learning and artificial intelligence techniques to solve real-world problems in financial services. You will support the development, testing, and deployment of models within secure, on-premises and/or cloud environments, contributing to initiatives in customer deepening opportunities, fraud detection, credit risk, customer segmentation, and operational efficiency.
Internship Duties and Responsibilities
Assist in building and validating machine learning models for banking use cases such as risk scoring, transaction classification, and customer behavior analysis. Work with structured and unstructured data from internal banking systems to prepare datasets for modeling. Support the deployment of models in on-premises environments using tools like Python, Docker, and internal APIs. Collaborate with data engineers, business analysts, and compliance teams to ensure models meet regulatory and operational standards. Document model development processes, assumptions, and performance metrics. Participate in code reviews, testing, and troubleshooting of deployed models. Stay informed about emerging trends in AI/ML and their applications in banking. Required Skills and Qualifications
Internship Required Technical Qualifications
Currently pursuing a bachelor’s degree in Computer Science, Data Sc
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