2027 Model Risk Software Engineering Intern - Southlake Only

Your Opportunity At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together.

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in Southlake, TX. The Model Risk Oversight (MRO) Internship Program within Corporate Risk Management provides hands-on experience supporting the oversight, validation, governance, and technology capabilities that help ensure quantitative and predictive models are reliable, well governed, and appropriately controlled.

Candidates considered through this sourcing requisition may be aligned to one of three available roles based on skills, interests, location, business need, and hiring alignment: Model Risk Governance Intern, Model Risk Validation Intern, or Model Risk Software Engineering Intern.

Internship dates are June 7, 2027 through August 6, 2027. Available Roles Model Risk Software Engineering Intern | Southlake, TX Contribute to technology solutions used by model validators and researchers across the organization.

Support the development of tools and applications that enhance validation processes, document software and workflows, and explore emerging technologies including artificial intelligence.

• Develop tools and applications that support model validation teams. • Solve technical problems and contribute accurate, well-documented code and technical documentation.

• Explore artificial intelligence, machine learning, and large language model technologies. • Learn new technologies, tools, and processes while collaborating with model risk partners.

What you have Education and Graduation Requirements • All three roles require current enrollment in a graduate degree program in a technical, quantitative, or closely related field.

• Model Risk Governance: Master’s degree with a planned graduation date between August 2027 and June 2028. • Model Risk Validation: Graduate degree in a field involving predictive modeling, financial engineering, economics, statistical analysis, applied mathematics, operations research, data science, or a related discipline; expected graduation date of December 2027 or later.

• Model Risk Software Engineering: Graduate degree in a technical or quantitative field. Preferred graduation timing for this sourcing requisition is December 2027 or later.

Required Qualifications • Authorized to work in the United States on a full-time basis without employer sponsorship. • Interest in model risk management, model validation, model governance, software engineering, quantitative analytics, artificial intelligence, or intelligent automation, based on role alignment.

• For Model Risk Validation and Model Risk Software Engineering, proficiency in 2+ of the following: Python, R, SAS, C#, C++, Java, or SQL. • For Model Risk Governance, interest in applying artificial intelligence, machine learning, generative AI, or intelligent automation within a regulated financial services environment, plus the ability to translate business-process requirements into automated workflows.

• Demonstrated analytical thinking, structured problem solving, and the ability to evaluate information, risks, technical challenges, or process requirements.

• Strong attention to detail and the ability to produce accurate, traceable documentation, code, or technical work products. • Ability to communicate technical concepts, findings, recommendations, and progress clearly and professionally.

• Ability to manage assigned work through completion, collaborate effectively, and learn new concepts, tools, technologies, processes, or regulatory expectations quickly.

Preferred Qualifications • Experience applying analytical, statistical, modeling, programming, automation, or data-related skills through coursework, research, internships, personal projects, or work experience.

• Exposure to artificial intelligence, machine learning, generative AI, large language models, or AI automation technologies. • Experience developing or deploying software, contributing to technical solutions, or documenting software development processes.

• Experience documenting analysis, research, testing results, technical findings, prompts, workflows, or quality assurance criteria for review by others.

• Interest in working at the intersection of model risk, governance, analytics, technology, and financial services.