Data Scientist

Company:Driven Brands

We invite you to join us at Driven Brands!

Headquartered in Charlotte, NC, Driven Brands (NASDAQ: DRVN) is the largest automotive services company in North America, providing a range of consumer and commercial automotive needs, including paint, collision, glass, vehicle repair, oil change, maintenance and car wash.

With over 4,500 centers in 15 countries, Driven Brands is the parent company of some of North America’s leading automotive service brands including Take 5 Oil Change, Take 5 Car Wash, Driven Glass, Meineke, Maaco, CARSTAR, and more.  Our network services over 50 million vehicles annually and generates more than $5 billion in system-wide sales each year.

Our culture inspires high performance and innovation, enabling our employees to go further, faster in their careers. With amazing people and great brands, we confidently look forward to exciting growth ahead, and believe in following the values that support this vision.

JOB DESCRIPTION:

CARSTAR is seeking an experienced and highly analytical Data Scientist who is passionate about leveraging data science techniques to drive business insights and innovation. The ideal candidate is skilled in machine learning, predictive analytics, and data modeling, with a strong ability to develop and deploy models that forecast outcomes and optimize business performance.

This role combines traditional data analysis with machine learning and model development, enhancing our ability to generate predictive insights. It involves working closely with the Data Ops team to design and integrate data models from multiple sources using BigQuery. The candidate will be responsible for building and optimizing data pipelines, writing efficient queries in BigQuery, and ensuring the seamless flow of data to QlikSense for reporting and visualization.

The role demands proficiency in Python, R, or SQL, experience with BI tools, and strong knowledge of ML algorithms, statistical modeling, data integration, and ETL processes. Expertise in data wrangling, integration, and delivering analytical insights is essential.

Specific Responsibilities:

• Develop and deploy machine learning models to identify patterns, forecast business outcomes, and optimize strategies.
• Conduct predictive analytics to support data-driven decision-making and uncover new business opportunities.
• Collaborate with the Data Ops team to build and integrate data models from multiple sources using BigQuery.
• Write and optimize queries in BigQuery to support data extraction, integration, and reporting needs.
• Create and maintain BI dashboards (QlikSense, Power BI, or equivalent) to visualize insights.
• Ensure data flows effectively into QlikSense for real-time reporting and visualization.
• Leverage Python, R, or ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) to build and refine models.
• Build strong relationships with Operations, Insurance, Finance, and Data Ops & BI teams, collaborating to deliver integrated data solutions.
• Present findings and recommendations at regional meetings and conferences, translating complex analytics into clear, actionable insights.
• Stay current with emerging data science trends and recommend new techniques or tools to enhance analytics capabilities.
• Contribute to team success by achieving related goals and results as needed.
• Perform other duties as reasonably assigned.

Qualifications:

• Degree in Mathematics, Statistics, Data Science, Computer Science, or a related field.
• 8+ years of hands-on experience in data science, machine learning, and advanced analytics.
• Proven experience building and deploying predictive models and performing statistical analysis.
• Strong proficiency in Python, R, or ML tools
• Extensive experience working with BigQuery for data integration, modeling, and querying.
• Strong SQL skills for data extraction, transformation, and analysis are a plus.
• Demonstrated ability to create data visualizations and reports using BI tools (QlikSense, Power BI, Tableau).
• Experience in building data pipelines and integrating data sources into reporting platforms.
• Strong quantitative and analytical skills, including sourcing, structuring, and automating data analysis.
• Ability to simplify technical topics for both technical and business stakeholders.
• Advanced proficiency in Excel and PowerPoint.
• Excellent verbal and written communication skills with effective presentation abilities.
• Proven ability to influence cross-functional teams and drive the adoption of data science solutions.
• A motivated self-starter with a proactive mindset, able to work independently and collaboratively.

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