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Lithia & Driveway

Is this your company?

Don't do it. - Anonymous employee Lithia & Driveway Employee Review

1.0
May 29, 2018
Anonymous employee
Recommend
CEO approval
Business Outlook

Pros

Coworkers are awesome and hardworking. The only notable benefit is the employee stock purchase plan.

Cons

Out of touch with the current job market/world. Pay is 20%+ below market average across the board, raises are 1-2% if at all. Look elsewhere if the position requires any kind of degree because they don't pay enough to justify the degree. PTO is a joke. No PTO for the first year. 40 hours PTO for the second year, PTO and sick time are shared. No accrued sick time after the first year. If you get sick say goodbye to your PTO time. Can't afford to take personal time off because the pay is too low. Benefits are nothing to write home about. Everything is paid nothing is given, which is fine but options are limited and poor. Shareholders are more important than employees driving profits. Management is always trying to cut costs at every corner which sacrifices quality of work done. Actions speak louder than words when it comes to culture and core values, the core values are seeded in every corporate email but never held up. It's a joke.

Explore other reviews about Lithia & Driveway

5.0
Jun 6, 2026
Recommend
CEO approval
Business Outlook

Pros

Love what I do. Great team members.

Cons

Very Hot on summer days.

5.0
May 15, 2026
Recommend
CEO approval
Business Outlook

Pros

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.

Cons

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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