Data Scientist - AI & Analytics (Entry)

Dealer Tire, LLC; California (MO); Hybrid; USD 81,000 - 110,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Paid time off

401k match

Job summary

Dealer Tire is seeking a data science professional to perform advanced modeling and analytics, delivering timely results and translating findings for stakeholders. The role focuses on building and validating ML models, exploring data with notebooks, and contributing to data science products and workflows.

You will work with Python, SQL, and modern data platforms, while applying best practices in governance and collaboration with cross-functional partners.

Qualifications

• BS in a quantitative field or related; advanced degree preferred.
• 0–2 years in data science or analytics, or advanced degree.
• Proficiency in SQL and relational data systems.
• Familiarity with Snowflake, dbt, or modern data platforms is a plus.
• Exposure to AI tools and prompt engineering concepts is a plus.

Responsibilities

• Perform Advanced Modeling & Analysis on data science projects with defined scope.
• Develop and implement statistical and machine learning models (regression, classification, clustering, forecasting).
• Apply analytical methods based on problem definitions, datasets and evaluation criteria.
• Utilize notebooks to explore data, prototype models and validate approaches.
• Contribute to Data Science Products and pipelines; write SQL and Python data transformations.
• Assist in documenting data science processes and model governance.

Skills

Python programming

SQL proficiency

Strong analytical thinking

Education

Bachelor’s degree in Business, Math, CS, Engineering

Advanced degree in quantitative field preferred

Tools

Python libraries: scikit-learn, pandas, numpy

Snowflake

dbt

Git

Job description

Dealer Tire is seeking a data science professional to perform advanced modeling and analytics, delivering timely results and translating findings for stakeholders. The role focuses on building and validating ML models, exploring data with notebooks, and contributing to data science products and workflows.

You will work with Python, SQL, and modern data platforms, while applying best practices in governance and collaboration with cross-functional partners.