Lead Data Scientist

Lead and Inspire

Guide a team of data scientists to tackle AutoZone’s most pressing challenges.

Collaborate and Strategize

Work closely with leaders to understand needs, develop directives, and manage projects.

Stakeholder Collaboration

Work with various departments to understand their data needs and present findings to senior management.

Innovate with Data

• Build predictive models using machine learning and other techniques to support new initiatives.

Analyze and Explore

• Validate, manipulate, and perform exploratory data analysis on large datasets.

Utilize Cutting-Edge Tools

• Work with Python, SAS, and other analytic computing environments to handle big data.

Research and Develop

• Create innovative statistical models for data analysis.

Communicate Insights

• Present findings to stakeholders and leadership, including the executive committee.

Drive Business Processes

• Implement analytics for smarter business processes and meaningful insights.

Stay Current

• Keep the team updated with the latest technical and industry developments.

Strategize Data Integration

• Identify and integrate new datasets to leverage system capabilities.

Execute Experiments

• Conduct analytical experiments to solve problems and make impactful decisions.

Mine Data

• Identify relevant data sources, collect large datasets, and perform data mining.

Develop Algorithms

• Create algorithms and models to mine big data, improve models, and ensure data accuracy.

Analyze Trends

• Interpret data for trends and patterns with clear objectives.

Collaborate for Implementation

• Work with software developers and machine learning engineers to implement models into production.

Project Management

• Develop and manage project plans, ensuring timely delivery and alignment with business goals.

Experience

10+ years in data science and 2+ years in project management.

Technical Skills

• Proficiency in data mining, mathematics, statistical analysis, pattern recognition, and predictive modeling.

Tool Proficiency

• Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (Java, R, Python, SAS).

Dynmic Environment

Comfort working in a research-oriented group with multiple concurrent projects.

Educational Background

Bachelor’s degree in statistics, applied mathematics, economics, or related discipline; Master’s degree preferred.