AI Intern - Summer 2027 - Dallas, TX or Franklin, TN at Nissan in Irving, TX

  • Company: Nissan
  • Location: Irving, Texas - United States of America
  • Job type: internship
  • Workplace: onsite
  • Posted: 2026-10-27

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Job description

Location(s): Dallas, TX or Franklin, TN Job Schedule: Full-time, 12-week program Degree Level: Junior or Senior Preferred Degree: Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, Data Analytics, Information Systems, Engineering, or a related field Sponsorship: Not Available Shape the Future of Mobility at Nissan: Launch Your Career, Drive Innovation We are currently looking for an AI Intern to join our team in Dallas, TX or Franklin, TN. Our team manages technology systems and applications supporting Nissan's Sales Finance companies across the United States and Canada. We are responsible for delivery and operations across core lending systems while also supporting customer and dealer systems, data quality initiatives, and artificial intelligence solutions. This internship opportunity will be within the Data Quality & AI team, where the selected candidate will develop predictive AI models to support NMAC portfolio risk analysis. The intern will work closely with the NMAC Risk team and may have the opportunity to present their solutions and findings to senior leaders, including the VP of Operations and President. A Day in the Life: Develop predictive AI and machine learning models to support portfolio risk analysis and business decision-making. Build Early Warning Vintage Monitoring models to improve loss forecasting and proactive risk detection. Develop forecasting and planning models to enhance lifetime loss projections and net credit loss forecasts. Perform data quality assessments, feature engineering, and analysis of large datasets to identify meaningful risk indicators. Partner with Risk, Operations, and Technology teams to translate portfolio behavior into actionable model features and business insights. Present project outcomes, recommendations, and analytical findings to business stakeholders and leadership. Who We’re Looking For: Required: Must be currently enrolled in an undergraduate or graduate degree program in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, Data Analytics, Engineering, Information Systems, or a related field. Students entering their Junior or Senior year at the start of the upcoming academic term. Strong experience with Python, SQL, scikit-learn, XGBoost, and statistical modeling techniques. Experience with data quality analysis, feature engineering, and working with large datasets. Ability to build models related to delinquency, default probability, loss forecasting, prepayment behavior, and portfolio risk segmentation. Knowledge of model validation, back-testing, bias and fairness assessments, drift monitoring, and model explainability techniques. Strong analytical, problem-solving, and communication skills. GPA of 3.0 or above (Candidates will be required to provide an official or unofficial transcript during the application process for verification.) Ability to perform work onsite in Dallas, TX or Franklin, TN. Preferred: Experience working with cloud and data platforms such as Snowflake, AWS, or similar technologies. Exposure to predictive analytics, machine learning, and artificial intelligence applications in financial services. Experience developing risk models, forecasting solutions, or analytical tools using large-scale datasets. Ability to translate complex analytical findings into clear business recommendations. Interest in risk management, portfolio analytics, auto finance, or financial technology. What You’ll Look Forward to at Nissan: Connection and Collaboration: We offer Business Synergy Teams (ERGs) and opportunities for our employees to strengthen their relationships and meet people from similar and diverse backgrounds to foster a culture of belonging. Professional Training and Development: Expand your knowledge and skills through Nissan’s rich innovation offerings, seminars, learning platforms, and leadership trainings. Nissan is committed to a drug-free workpl

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