[Hiring] Associate Data Scientist @Dealer Tire

Role Description

As an Associate Data Scientist, your essential job functions will include the following:

• Perform Advanced Modeling & Analysis
  • Execute assigned data science projects with defined scope, delivering accurate and timely results.
  • Develop and implement statistical and machine learning models under guidance, including regression, classification, clustering, and forecasting techniques.
  • Apply appropriate analytical methods based on provided problem definitions, datasets, and evaluation criteria.
  • Utilize interactive development environments (e.g., notebooks) to explore data, prototype models, and validate approaches.
  • Interpret model outputs and assist in translating findings into actionable insights for stakeholders.
  • Leverage AI-assisted development tools to accelerate analysis, research, and code development.
• Perform AI Engineering
  • Utilize AI tools and large language models (LLMs) to support analysis, code generation, and research tasks.
  • Apply basic prompt engineering techniques to improve outputs from AI-assisted workflows.
  • Assist in building simple AI-enabled workflows or components under guidance.
  • Develop familiarity with emerging AI techniques and their application within data science workflows.
• Contribute to Data Science Products
  • Contribute to the development and maintenance of data science products, including models, pipelines, and reporting.
  • Support implementation of model training, evaluation, and output generation workflows.
  • Assist in documenting data science processes, model assumptions, and system behavior.
  • Generate regular reporting and analysis to support performance monitoring of data science products.
  • Communicate progress and results to team members and stakeholders as needed.
• Manage Large Datasets – Cleaning, Transforming, Understanding
  • Clean, transform, and prepare large structured and unstructured datasets for analysis and modeling.
  • Write SQL and Python-based transformations to create usable datasets from raw data sources.
  • Work with Snowflake and dbt workflows to support development of analytics-ready datasets.
  • Assist in developing and maintaining data pipelines used in modeling workflows.
  • Perform exploratory data analysis to understand data characteristics, distributions, and potential issues.
• Data Science Quality and Governance
  • Follow established software development best practices, including version control, documentation, and testing standards.
  • Write clear, maintainable, and testable code for data science workflows.
  • Assist in validating datasets, model outputs, and reporting results for accuracy and consistency.
  • Participate in code reviews, focusing on syntax correctness and general structure.
  • Ensure reproducibility of analyses through proper documentation and organization of work.
• Technology and Technical Development
  • Develop proficiency in Python as the primary programming language and use R where appropriate for statistical analysis.
  • Utilize standard data science libraries and frameworks (e.g., scikit-learn, pandas, numpy).
  • Begin developing modular code practices and reusable functions.
  • Gain familiarity with containerization (e.g., Docker) and deployment concepts.
  • Use AI-assisted tools to improve development speed and code quality.
• Thought Development and Collaboration
  • Build foundational business acumen by understanding how data science outputs support business decision-making.
  • Communicate findings and progress clearly with team members and stakeholders.
  • Seek feedback and continuously improve technical and analytical skills.
  • Collaborate effectively with other Data Scientists, Analytics Engineers, and business partners.
• Build Trust and Reputation for Data Science
  • Deliver accurate, reliable, and well-documented analytical outputs.
  • Support team members by providing consistent, high-quality work.
  • Develop expertise in assigned datasets, tools, and processes.
  • Build strong working relationships within the Data Science team and with cross-functional partners.

Qualifications

• Bachelor’s degree in Business, Mathematics, Computer Science, Engineering, or related field.
• Advanced degree in a quantitative field preferred.
• 0–2 years of experience in data science, analytics, or related roles -OR- advanced degree.
• Ability to work in a fast-paced environment with a strong sense of urgency.
• Strong intellectual curiosity and desire to learn.

Requirements

• Strong foundational programming skills in Python; familiarity with R is a plus.
• Basic understanding of statistical modeling and machine learning concepts.
• Proficiency in SQL and experience working with relational data systems.
• Familiarity with Snowflake, dbt, or modern data platforms is a plus.
• Exposure to version control practices (Git) and development workflows.
• Familiarity with data science libraries (e.g., scikit-learn, pandas) is a plus.
• Exposure to AI tools and prompt engineering concepts is a plus.

Benefits

• Competitive & comprehensive benefit package including: paid time off, medical, dental, vision, and 401k match (50% on the dollar up to 7% of employee contribution).
• Sign on bonus is subject to state and local laws, terms and conditions, including employment status and length-of-service requirements.