It's a great company to work for - Recensione dipendente - General Manager presso Lithia & Driveway

5,0
13 ott 2025
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Working for Lithia has been an incredible experience. In just two years, I’ve learned more about the automotive business, leadership, and customer experience than I ever expected. The company provides a clear structure, strong support, and countless opportunities for growth if you’re willing to put in the work. The culture here is high-energy, team-oriented, and built around performance and accountability. Leadership genuinely wants to see people succeed and gives you the tools and autonomy to make that happen. Lithia’s national presence also opens the door to endless career paths, both within your store and across the company.

Svantaggi

The pace can be demanding, and expectations are high, but if you’re driven and goal-oriented, you’ll thrive here.

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Risposta di Lithia & Driveway
7mo
Thank you for taking the time to share your experience. We’re thrilled to hear that you value our collaborative culture and the opportunities for growth here.

Esplora altre recensioni su Lithia & Driveway

5,0
6 giu 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Love what I do. Great team members.

Svantaggi

Very Hot on summer days.

5,0
15 mag 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Strong exposure to real business data from automotive sales, finance, inventory, and customer operations. Opportunity to work on high-impact analytics that directly affect dealership performance and revenue. Large-scale company with many datasets and business units, which is good for learning business intelligence and predictive analytics. Growing digital transformation initiatives can provide opportunities to work with modern analytics tools and automation.

Svantaggi

Legacy systems and fragmented data sources may make data cleaning and integration challenging. Traditional corporate structure can sometimes slow down decision-making or the implementation of data-driven ideas. Work may lean more toward reporting/dashboarding than advanced machine learning, depending on the team. Stakeholders may prioritize quick operational insights over long-term data science experimentation. A high-pressure retail environment can lead to tight deadlines and rapidly changing priorities.

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