Data Scientist Co-op

Cox Enterprises; Atlanta (GA); Hybrid; USD 25,000 - 39,000; Part time

Benefits offered by this job

Mentorship

Hybrid work model

Real-world projects

Multiple-term co‑op

Job summary

Cox Enterprises is seeking a Data Scientist Co-op on the SSE team within Decision Support. This multi-term internship combines business insight, math, AI, and software engineering to deliver data-driven decisions across automotive data and logistics problems.

You will learn end-to-end data science—from framing questions to communicating results—under mentorship, with increasing responsibility across terms and a path to future opportunities. Hybrid in-office presence is required.

Qualifications

• Currently enrolled in a Bachelor’s program in a quantitative field such as CS, DS, Statistics or IE.
• Able to commit to multiple co-op terms as per university model.
• Foundational Python skills from coursework or projects.

Responsibilities

• Assist data scientists with exploring, cleaning, and preparing data from internal sources for analysis and modeling.
• Write Python and SQL to extract, transform, and analyze data using team tools.
• Help build, test, and tune machine learning models under guidance.
• Support prototypes, demos, and visualizations showing how data and AI solve business problems.
• Document work clearly for reproducibility.
• Present findings to team and partners with appropriate audience level.

Skills

Python

SQL

Pandas/NumPy

Data visualization

Education

Bachelor’s degree in CS/DS/Statistics/Industrial Engineering

Tools

Snowflake

AWS

Git

Job description

Intern/Co-Op sessions are considered temporary employment. No full-time employment commitments are made. However, depending on our business needs, some interns may be considered for a full-time position following the conclusion of the session conditioned upon the intern graduating from their academic program and being available to commence full-time employment at a specified time.

JOB SUMMARY

The Decision Support organization turns Inventory Solutions' most complex questions into fast, confident decisions, combining business knowledge, mathematics, AI and machine learning, and software engineering to produce the models, applications, and platforms behind those decisions. Within Decision Support, the Strategic Solutions & Enablement (SSE) team sets the shared architecture, tooling, and methodology standards used across the organization and builds the internal-facing decision surfaces teams rely on across areas like transaction intelligence, logistics decisioning, and operational optimization.

As a Data Scientist Co-op on the SSE team, you will work alongside experienced data scientists and engineers on real projects that support business decision-making. This is a multi-term co‑op designed to give a student progressively deeper hands‑on experience across several terms. You will learn how production data science is done end to end — from framing a business question, to exploring data, to building and validating models, to communicating results — under the guidance and mentorship of the team. You are not expected to own products independently; you are expected to be curious, learn quickly, and contribute meaningfully to the team's work.

PRIMARY DUTIES / KEY RESPONSIBILITIES

Learning & Applied Analytics

• Assist data scientists in exploring, cleaning, and preparing data from a variety of internal sources for analysis and modeling.
• Write Python and SQL to extract, transform, and analyze data, building your proficiency with the team's tools and standards.
• Help build, test, and tune machine learning models under guidance, learning classical methods (e.g., regression, gradient boosting, clustering) and applied generative AI approaches.
• Support the creation of prototypes, demos, and visualizations that show how data and AI can be used to solve business problems.

Collaboration & Communication

• Participate in team standups, design discussions, and code/peer reviews, gradually taking on more responsibility across terms.

• Document your work clearly so it can be understood, reproduced, and built on by the team.

• Present findings and progress to the team and, over time, to business partners, adjusting depth for the audience

.

Growth Across Terms

• Return across multiple co‑op terms, alternating semesters, building continuity and increasing scope and independence with each term.
• Apply feedback and coursework to progressively more substantial contributions to SSE projects.

MINIMUM QUALIFICATIONS

• Currently enrolled in a Bachelor's degree program in Computer Science, Data Science, Statistics, Industrial Engineering, or a related quantitative field.

• Able to commit to multiple co‑op terms, alternating semesters, per a standard university co‑op model.

• Foundational Python programming skills (e.g., coursework or projects using Pandas, NumPy, or scikit-learn).

• Working knowledge of SQL and an 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 a demonstrated ability to learn quickly and work as part of a team.

• Clear written and verbal communication skills

.

PREFERRED QUALIFICATIONS

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

CORE VALUES & 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.

WHY JOIN OUR TEAM

• Get real, hands‑on data science experience on products that operating teams use daily to make decisions.
• Work with modern cloud-native platforms (Snowflake, AWS, Bedrock), applied AI tooling, and rich automotive data at scale.
• Learn directly from experienced data scientists and engineers who mentor through doing, not just formal training.
• Build continuity and depth across multiple terms, with a genuine path toward future full‑time opportunities.

Travel: 0-10%

Hybrid – ability to work in-office 1-3 days per week.