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Lithia & Driveway

Is this your company?

Dont ever try this! - Finance Manager Lithia & Driveway Employee Review

1.0
Oct 9, 2011
Recommend
CEO approval
Business Outlook

Pros

Good Structure, management is fun at times but very snooty and only care about themselves when it comes down to it. Not too much in the Pro section sorry its a truly sucky job.

Cons

Underpaid compared to other companies, old car dog sales people are very dishonest. Everyone backstabs each other to upper management for favoritism in getting a car deal done. Unethical practices are common company wide and are not talked about but are encouraged to keep your job. Hours are usually 60 to 70 hours plus the nights you stay up worrying about things in bed. Corporate sets unattainable goals that MUST be maiintained each month or you get laughed at in front of all management from parts,service,body shop and office in there weekly meeting and then are on the chopping block! Negoitating needs to get out of the 80's people are more informed its time to change the program SID!

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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