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Lithia & Driveway

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Corporate nightmare - Anonymous employee Lithia & Driveway Employee Review

2.0
Feb 25, 2020
Anonymous employee
Recommend
CEO approval
Business Outlook

Pros

Loved my coworkers, easy to find mentors, enjoyed the actual work, good desk space, good IT support, nice office, well executed intern program

Cons

Poor leadership and management, lack of transparency, zero real culture Overall there is a lot of talk about culture & values but very little follow through where it actually matters. They boast about "work life balance" on their career website but provide the bare minimum for any sort of PTO or family time. "Improve constantly" but will only truly make (or listen to) improvements if you are a male in a senior leadership position. There were tons of women in lower management positions and yet barely any in senior... "Take personal ownership" and yet their leaders who were constantly being complained about + losing team members left and right, stay in their positions because they are most likely related to someone high up in the company. Never met anyone there who seemed to love their job or role at the company.

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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