Associate Data Scientist
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Job Description
Associate Data Scientist at Dealer Tire performing advanced modeling and analysis. Collaborating and contributing to the development of data science products and workflows.
Responsibilities:
- 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
- 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 the development and maintenance of data science products, including models, pipelines, 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
- 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
- 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
- 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
- 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
- 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
Requirements:
- 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
- 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:
- paid time off
- medical
- dental
- vision
- 401k match (50% on the dollar up to 7% of employee contribution)
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