Lead Data Scientist: Strategy, ML & Insights

AAA; Coppell (TX); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health coverage

401(k) matching + Pension

Tuition assistance

Floating holidays & PTO

Parental leave

Wellness programs

Employee discounts

Job summary

Auto Club Enterprises is seeking a Lead Data Scientist to act as an internal consultant, solving business problems with data to improve efficiency and member experience. You will analyze large datasets, build predictive models, and deploy data-driven solutions in collaboration with engineers and stakeholders.

The role emphasizes mentoring, project leadership, and translating complex analytics into clear business insights for non-technical audiences. Hybrid work with on-site presence required.

Qualifications

• Bachelor’s degree in a quantitative field is required.
• 3+ years of professional data science analytics experience.
• 1+ year leading projects or mentoring teammates.
• Strong SQL and Python programming for analysis.
• Experience with cloud platforms and modern data ecosystems.

Responsibilities

• Partner with stakeholders to translate business problems into analytical plans.
• Pull, curate, and analyze data from enterprise platforms to deliver actionable insights.
• Develop, validate, deploy, and monitor ML models in production.
• Create dashboards and visuals with Tableau or Power BI to communicate findings.
• Lead projects and mentor junior data scientists, guiding cross‑functional work.

Skills

Statistics

Data analysis

Machine learning

Experiment design

Communication

Project leadership

Education

Bachelor’s degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics, or related quantitative field

Tools

SQL

Python

Tableau

Power BI

AWS

GCP

Databricks

Snowflake

Job description

Auto Club Enterprises is seeking a Lead Data Scientist to act as an internal consultant, solving business problems with data to improve efficiency and member experience. You will analyze large datasets, build predictive models, and deploy data-driven solutions in collaboration with engineers and stakeholders.

The role emphasizes mentoring, project leadership, and translating complex analytics into clear business insights for non-technical audiences. Hybrid work with on-site presence required.