Summer 2027 AI/ML Modeler Intern

About the role

This paid 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.

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 Qualifications

Technical

• Currently pursuing a bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• Familiarity with Python and ML libraries (e.g., Scikit-learn, Pandas, NumPy).
• Basic understanding of machine learning concepts and supervised/unsupervised learning techniques.
• Exposure to version control tools (e.g., Git) and containerization (e.g., Docker).
• Strong analytical and problem-solving skills.
• Ability to work in a secure, regulated environment with attention to data privacy and compliance.

Soft Skills

• Strong communication skills – able to explain technical concepts to non-technical stakeholders clearly and concisely.
• Team collaboration – comfortable working in cross-functional teams and contributing to group problem-solving.
• Adaptability – open to learning new tools, methods, and responding to changing project requirements.
• Attention to detail – meticulous in data handling, documentation, and model validation.
• Time management – able to prioritize tasks and meet deadlines in a fast-paced environment.
• Ethical mindset – understands the importance of fairness, transparency, and accountability in AI applications, especially in financial services.

Preferred Qualifications

• Internship or academic project experience in AI/ML or data analytics.
• Knowledge of SQL and experience working with relational databases.
• Understanding of banking operations or financial services is a plus.
• Experience with cloud and/or on-premises deployment tools or enterprise IT environments.

Learning Objectives

• Mentorship and training in AI/ML development within the banking sector.
• Opportunities to work on impactful projects that improve customer experience and operational efficiency.
• A collaborative and inclusive team environment.
• Career development and growth within a leading financial institution.