2027 TFS Data Science Internship

Toyota North America•Plano, TX

7d•Onsite

About The Position

Toyota Financial Services (TFS) is seeking highly motivated graduate students interested in technology, financial services, and the automotive industry for its Data Science Internship Program. The approximately 12-week internship takes place at Toyota Headquarters in Plano, Texas, from May through August 2027. The program provides on-the-job experience, networking, and mentorship. Strong performers may have the opportunity to return for full-time positions. The intern will uncover actionable insights through data analysis and support data-based decision-making throughout the customer lifecycle. Work may support areas including Sales and Marketing, Credit Risk, Residual Value, Customer Management and Collections, Finance and HR, Insurance, or Manufacturing. Projects may include credit-risk model development and validation, pricing tests for hourly vehicle rentals, and analysis of interest-rate reduction tests. Toyota does not provide immigration-related employment visa or work authorization sponsorship for this role. Applicants must be authorized to work in the United States without Toyota sponsorship now or in the future.

Requirements

Be within one year of completing a Master's or Ph.D. in a heavily analytical discipline.
Have advanced hands-on experience with tools such as Python (NumPy/Pandas), scikit-learn, R, and/or SQL.
Have experience using statistical and machine-learning techniques to solve problems.
Be able to solve problems, think outside the box, and demonstrate a passion for learning and growth.
Be able to present analysis results and make recommendations to leadership.
Be at least 18 years of age.
Have reliable transportation.
Have authorization to work in the United States without Toyota immigration-related employment sponsorship now or in the future.
Have a minimum GPA of 2.7.

Nice To Haves

Exposure to and familiarity with Logistic Regression, Time Series Analysis, Experimental Design, Generalized Linear Models, Mixed Modeling, Multivariate Statistics, Large-Scale Predictive Modeling, CHAID/decision trees, Gradient Boosted Trees, Random Forests, and Neural Networks.

Responsibilities

Partner with business teams to identify important questions about customers and their value.
Extract and wrangle data from internal and external systems using tools such as SQL, Python, and R.
Analyze data and build models using advanced analytics methods and statistical software.
Develop, manage, and deploy analytic solutions using tools such as R and Python.
Create PowerPoint presentations recommending business decisions.
Visualize findings through fixed reports and tools such as Tableau or Power BI.
Develop analytical project plans and coordinate information flows with upstream and downstream teams.
Attend and participate, where appropriate, in project planning and prioritization sessions.