Data Science Intern

Data Scientist Intern

See What We’re All About

As the fastest-growing distributor of restaurant equipment, HVAC and residential appliance parts, we like to do things a little differently. First, you need to understand and demonstrate our Core Values with safety being your first priority. That’s key. But we’re also looking for unique enthusiasm, high integrity, courage to embrace change…and if you know a few jokes, that puts you on the top of our list!

Do you have a genius-level knowledge of original equipment manufacturer parts? If not, no problem! We’re more interested in passionate people with fresh ideas from different backgrounds. That’s what keeps us at the top of our game. We’re proud that our workplace has been recognized for its growth and innovation on the Inc. 5000 list 15 years in a row and the Crain’s Fast 50 list ten times. We are honored to be voted by our Chicagoland team as a Chicago Tribune Top Workplace for the last four years.

If you’re ready to roll up your sleeves, go above and beyond and put your ambition to work, all while having some fun, let’s chat – Apply Today!

Perks

• Parts Town Pride – check out our virtual tour and culture!
• Hybrid Work schedule
• Team member appreciation events and recognition programs
• Volunteer opportunities
• Casual dress code
• On-demand pay options: Access your pay as you earn it, to cover unexpected or even everyday expenses

The Job at a Glance
 

Join Red Lightning, Parts Town’s innovation hub, as a Data Scientist Intern, and be part of the future of AI in the service and parts industry. We’re looking for someone who is curious, creative, and driven to join our fast-paced innovation team for a 10-week internship where you’ll work on real-world challenges, testing and building AI models that will shape the next generation of smart services and digital tools.

This internship is ideal for those passionate about using AI to solve practical business problems - with an emphasis on experimentation, rapid prototyping, and cross-functional collaboration. Our goal is for you to build confidence and walk away with more knowledge and a clearer picture of where you want to go in your career.

A Typical Day

• Clean, prepare, and analyze structured and unstructured data from multiple sources (e.g., transaction logs, equipment signals, CRM).
• Identify trends, anomalies, and key features relevant to business objectives.
• Develop, test, and refine machine learning models to support use cases.
• Work closely with AI Engineers to turn insights into scalable solutions.
• Communicate findings through dashboards, visuals, and presentations.
• Own a mini project from exploration to insight delivery, with mentorship from the team.

To Land This Opportunity

• You’re working toward a Bachelor’s degree in one of the following fields: Data Science, Computer Science or Data Engineering
• Strong foundation in statistics, data exploration, and machine learning.

• Knowledge of Python and common data science libraries (e.g., pandas, scikit-learn, TensorFlow, matplotlib, seaborn).

• Familiarity with predictive modeling, time series analysis, anomaly detection, and classification techniques.
• Bonus: Exposure to NLP, LLM, or recommendation systems.
• You’re an all-star communicator and are proficient in English (both written and verbal)

About Your Future Team
 

At Parts Town, we value transparency and are committed to ensuring our team members feel appreciated and supported.   We prioritize our positive workplace culture where collaboration, growth, and work-life balance are celebrated. The pay for this internship is $17.00 per hour. Parts Town is a pay for performance-company. In addition to base pay, some roles offer a profit-sharing program, and an annual bonus depending on the role. Our comprehensive benefits package includes health, dental and vision insurance, 401(k) with match, employee assistance programs, paid time off, paid sick time off, paid holidays, paid parental leave, and professional development opportunities.

Parts Town welcomes diversity and as an equal opportunity employer all qualified applicants will be considered regardless of race, religion, color, national origin, sex, age, sexual orientation, gender identity, disability or protected veteran status.