Data Scientist I - Decision Support - Military Veterans

The Decision Support organization provides data-driven insights and advanced analytics solutions to inform operational, strategic, and product-related decisions across Cox Automotive. Within Decision Support, the Applied Research team specializes in developing and testing cutting-edge analytical methods for a broad range of use cases—such as vehicle information enhancement, fraud detection, and machine learning for digital auction solutions.
 
As a Data Scientist I on the Applied Research team, you will gain familiarity with essential data science concepts and techniques while contributing to high-impact projects under the guidance of senior team members. You’ll leverage Python, AWS, Snowflake, and various visualization tools (e.g., Tableau) to explore data, build basic models, and generate insights that drive smarter business decisions in the wholesale and retail automotive ecosystem. Strong collaboration, effective communication, and a foundation in analytical thinking will be critical for success in this entry-level data science role.

Key Responsibilities

1.     Foundational Data Science & Modeling

• With guidance from senior colleagues, participate in the design, development, and validation of data science models and algorithms that address key business challenges (e.g., vehicle pricing, fraud detection).

• Assist in testing and adapting existing algorithmic products, ensuring accuracy, reliability, and alignment with project requirements.

2.     Data Exploration & Preparation

• Gather and cleanse data from multiple sources (e.g., AWS S3, Snowflake) under the direction of more experienced team members.

• Conduct feature engineering and exploratory data analysis in Python/Jupyter to identify patterns and potential model inputs.

3.     Visualization & Reporting

• Create basic data visualizations (Tableau or equivalent) to communicate findings to internal stakeholders.

• Develop progress reports and status updates for management, clearly articulating emerging insights and project timelines.

4.     Collaboration & Knowledge Building

• Attend team and client meetings to understand business needs and project objectives, applying data science methods where relevant.

• Partner with senior data scientists and peers to refine analytical approaches, learn new methodologies, and troubleshoot data-related challenges.

• Share learnings and project updates in a clear, easily understood format, inviting feedback and iterative improvement.'

5.     Tooling & Process Adherence

• Follow established best practices in Python coding (scripts, notebooks) and version control.

• Learn and apply AWS (e.g., Lambda, S3) and Snowflake capabilities (e.g., queries, tasks) as part of data pipelines.

• Leverage UNIX experience to navigate servers, manage files, and run data processing jobs.

Minimum Qualifications

Education & Experience

• Bachelor’s degree in a related field (e.g., Computer Science, Data Science, Mathematics, Statistics, or Economics), or equivalent work experience.

• 3 years of relevant data science or analytics experience (internships or coursework projects encouraged).

Technical Skills

• Programming: Foundational knowledge of Python (preferably in Jupyter Notebooks); basic familiarity with UNIX command-line operations.

• Cloud & Data Warehousing: Exposure to AWS (Lambda, S3) and Snowflake (ability to run queries, familiarity with tasks/stored procedures) highly preferred.

• Visualization: Basic proficiency with Tableau or other BI tools to develop straightforward dashboards or charts.

• Data Management: Understanding of data wrangling, feature engineering, and the fundamentals of quality assurance.

• Modeling: Basic exposure to machine learning concepts (e.g. regression, classification, clustering) with the ability to develop simple predictive models under guidance and apply them to real-world or simulated datasets.

Domain Knowledge

• Automotive/auction industry experience a plus (e.g., understanding how vehicles flow through wholesale/retail channels).

• Familiarity with fraud detection concepts, or general machine learning for digital marketplaces, is a bonus.

Soft Skills

• Analytical Thinking: Able to interpret data patterns, break down business problems, and propose basic solutions.

• Business Acumen: Demonstrates an interest in how data science impacts the broader organization, with a curiosity about market and industry trends.

• Consulting: Willingness to understand client needs, adapt approaches, and communicate results in a meaningful way.

• Collaboration & Communication: Open to feedback, shares progress, and asks questions to ensure alignment with team goals.

 
Core Values & Behaviors

• Acts with Integrity: Adheres to ethical standards, organizational policies, and personal values, even under pressure.

• Builds Partnerships: Fosters trusting relationships with teammates and stakeholders, demonstrating flexibility to work across boundaries.

• Collaborates with Intent: Communicates effectively, adjusts style for diverse audiences, and welcomes feedback to drive better outcomes.

• Develops Trust: Practices transparency in work processes, embraces diverse viewpoints, and encourages open dialogue.

• Drives Innovation: Explores new ways to solve problems, experiments with novel ideas, and takes calculated risks to improve results.

 
Why Join Our Team?

• Contribute to real-world data science projects with immediate business impact in a fast-paced automotive marketplace.

• Collaborate closely with senior data scientists, engineers, and other professionals who will mentor and guide your development.

• Leverage cutting-edge tools and technology in cloud environments (AWS, Snowflake) and develop valuable skills in data visualization, machine learning, and analytics.

• Enjoy a supportive learning environment that values integrity, innovation, and cross-team collaboration.

 
This Data Scientist I role is an excellent opportunity for data science professionals to build a foundation in data science, gain domain knowledge in the automotive auction ecosystem, and grow their skill set under the mentorship of experienced team members within Decision Support and the Applied Research sub-team.

Travel : 0-10%