Toyota

Data Science Intern

USA internshipsAI/ML/DataNewPosted 2 days ago

Location: Plano, TX
Type: USA internships

About this role

From Toyota’s careers page.

Overview

Who we are

Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us.

Toyota does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future. You must have the right to work in the United States and not require Toyota support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, ‘job flexibility benefits’ [also known as I-140 or Adjustment of Status portability], etc.) now or in the future. You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future.

Who we are looking for:

Toyota Financial Services (TFS) Data Science team is looking for highly motivated, driven graduate students with an interest in technology, financial services, and the automotive industry to fill internship roles in our Data Science team.

The Data Science Internship Program is designed to provide a combination of on-the-job experience, networking, and mentorship, which are critical components for personal and professional growth. As a Data Science Intern, you will spend approximately 12 weeks at our Toyota Headquarters in Plano, TX gaining relevant work experience with a globally respected company. The program will run from May – August 2027. Strong performers are often given the opportunity to return for full-time positions.

Location:

Toyota Headquarters - Plano, TX

What you’ll be doing:

Through this internship, you will uncover actionable insights through data analysis and help drive data-based decision making throughout the customer lifecycle. You will have the ability to support one or more areas, including but not limited to: Sales and Marketing, Credit Risk, Residual Value, Customer Management and Collections, Finance & HR, or associated business including Insurance and Manufacturing.

Partner with the business to identify the most important questions that need to be answered about our customers and their value.
Hands on data extraction and data wrangling from internal and external systems using SQL, Python, R, etc.
Analysis and model building using advanced analytics tools and techniques using statistical software packages like Python, R, etc.
Develop, manage and deploy analytic solutions using statistical software packages like R, Python, etc.
Build PowerPoint presentations to recommend business decisions.
Create output and or results that visualize findings using fixed reports and or tools like Tableau/Power BI
Develop analytical project plans and integrate inflows and outflows of information with teams upstream and downstream from analytical efforts.
Attend and participate (where appropriate) in various project planning and prioritization sessions.

Projects may include:

Credit Risk Champion Challenger Model - create a new model to predict customer credit risk using a more advanced predictive algorithm to either find a better way of predicting customer credit risk or validate that the current model performs better than the proposed new model.
Price Testing for Hourly Vehicle Rentals - implement multiple pricing tests and analyzed the resulting data to learn the impact of various pricing strategies on the hourly rental business.
Interest Rate Reduction Test - implement a test where the interest rates charged in some areas of the country were reduced by a specified amount and the resulting data was analyzed using statistical methods to calculate the impact of the rate reduction on specific KPIs.

What you bring:

Within 1 year of completing a Master’s or Ph.D. in a heavily analytical discipline
Advanced hands-on experience with tools such as Python (NumPy/Pandas), scikit-learn, R, and/or SQL.
Experience in using a variety of statistical and machine learning techniques to solve problems.
Exposure and familiarity with topics like 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.
Ability to problem solve and think outside the box with a passion to learn and grow
Presenting analysis results and making recommendations to leadership

Required Qualifications

Must be 18 years of age or older
Must have reliable transportation
Must have the right to work in the United States and not require Toyota sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, or F-1 OPT extension) now or in the future
Minimum GPA of 2.7 or higher
Within 1 year of completing a Master’s or Ph.D. in a heavily analytical discipline

What we’ll bring

During your interview process, our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:

A work environment built on teamwork, flexibility and respect
Professional growth and development programs and opportunities

Belonging at Toyota

Our success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star.

Applicants for our positions are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law.

Have a question, need assistance with your application or do you require any special accommodations? Please send an email to talent.acquisition@toyota.com.

Apply nowOpens Toyota’s application page