Data Scientist Co-op

The Data Scientist Co-op role sits on Cox Automotive’s Strategic Solutions & Enablement (SSE) team within the Decision Support organization. This multi-term internship supports data exploration, model building and validation, and clear communication of results to enable business decision-making.

Role Focus

• Work with data scientists on data discovery, cleaning, preparation, and analysis for modeling efforts.
• Contribute to prototype development, demonstrations, and visualizations that support business use cases.
• Assist with machine learning model development, including testing and tuning under guidance.
• Learn and apply both classical modeling methods (regression, gradient boosting, clustering) and applied generative AI approaches.

Key Responsibilities

• Assist with exploring, cleaning, and preparing datasets from multiple internal sources for analysis and modeling.
• Write Python and SQL to extract, transform, and analyze data, building familiarity with team tools and standards.
• Help build, test, and tune machine learning models with support, progressing from foundational methods to applied generative AI.
• Support creation of prototypes, demos, and visualizations to demonstrate how data and AI solve business problems.
• Participate in standups, design discussions, and code or peer reviews, with increasing responsibility across co-op terms.
• Document work clearly so it can be understood, reproduced, and extended by the team.
• Present findings and progress to the team, and over time to business partners, with communication depth tailored to the audience.
• Return across multiple co-op terms, alternating semesters to build continuity and increase scope and independence.
• Apply feedback and coursework to take on progressively more substantial contributions to SSE projects.

Required Qualifications

• Currently enrolled in a Bachelor’s degree program in Computer Science, Data Science, Statistics, Industrial Engineering, or a related quantitative field.
• Ability to commit to multiple co-op terms, alternating semesters, consistent with a standard university co-op model.
• Foundational Python experience, including coursework or projects using Pandas, NumPy, or scikit-learn.
• Working knowledge of SQL and interest in learning cloud data platforms such as Snowflake and AWS.
• Exposure to statistics and/or machine learning concepts through coursework or projects.
• Strong analytical thinking and demonstrated ability to learn quickly and work collaboratively.
• Clear written and verbal communication skills.

Technologies and Tools

Python, SQL, Pandas, NumPy, scikit-learn, Snowflake, AWS, Bedrock, Tableau, Streamlit, Git, regression, gradient boosting, clustering.

Preferred Qualifications

• Coursework or personal or academic projects involving machine learning, generative AI, or data visualization (for example Tableau, Streamlit).
• Familiarity with version control (Git) and collaborative development practices.
• Interest in the automotive industry or large-scale marketplace data.

Location and Work Arrangement

• Location: Atlanta, GA 30328 (hybrid)
• Travel: 0–10%

Compensation

• Hourly pay rate range: $22.02 - $33.08 per hour.
• The hourly base rate may vary within the anticipated range based on location and the candidate’s knowledge, skills, and abilities.
• May be eligible for additional compensation, which may include commission (annual, monthly, etc.) and/or an incentive program.

Benefits

• Health care insurance (medical, dental, vision)
• Retirement planning (401(k))
• Paid days off including sick leave, parental leave, flexible vacation or wellness days, and/or PTO

Intern/Co-op Information

Intern/Co-op sessions are considered temporary employment. No full-time employment commitments are made.

Core Values and Behaviors

• Acts with Integrity: Adheres to ethical standards, organizational policies, and personal values.
• Builds Partnerships: Fosters trusting relationships with teammates and stakeholders.
• Collaborates with Intent: Communicates effectively and welcomes feedback to drive better outcomes.
• Develops Trust: Practices transparency and embraces diverse viewpoints.
• Drives Innovation: Explores new ways to solve problems and is willing to experiment and learn.