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Microsoft San Francisco, CA (US)

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Microsoft San Francisco, CA (US) Reviews

  • "Great company"

    StarStarStarStarStar
    • Work/Life Balance
    • Culture & Values
    • Diversity & Inclusion
    • Career Opportunities
    • Comp & Benefits
    • Senior Management
    Current Employee - Financial Analyst in San Francisco, CA (US)
    Current Employee - Financial Analyst in San Francisco, CA (US)
    Recommends
    Positive Outlook
    Approves of CEO

    I have been working at Microsoft full-time

    Pros

    diverse skill set, flexibility to switch roles, high visibility

    Cons

    no guarantee to get top choice role

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Microsoft San Francisco, CA (US) Photos

Microsoft photo of: HQ Lounge Area
Microsoft photo of: HQ Entry
Microsoft photo of: Snacks and Sips
Microsoft photo of: Conference Room
Microsoft photo of: TARDIS 2.0
Microsoft photo of: Desk Area

Microsoft San Francisco, CA (US) Jobs

Microsoft San Francisco, CA (US) Salaries

Salaries in $ (USD)
Average
Min
Max
116 salaries
$149,771 per year
$60k
$254k
$149,771 per year
$60k
$254k
$131,167 per year
$84k
$177k
$131,167 per year
$84k
$177k
$157,722 per year
$131k
$185k
$157,722 per year
$131k
$185k

Microsoft San Francisco, CA (US) Interviews

Experience

Experience
67%
12%
21%

Getting an Interview

Getting an Interview
39%
20%
20%
15
4
2

Difficulty

3.0
Average

Difficulty

Hard
Average
Easy
  1.  

    Genetics Research Interview

    Anonymous Employee in San Francisco, CA (US)
    Accepted Offer
    Positive Experience
    Average Interview

    Application

    I interviewed at Microsoft (San Francisco, CA (US)) in February 2021.

    Interview

    I went through 4 stages. The first was a call with the hiring manager to review my background. It was mostly behavioral questions. Then I had two one-on-one technical interviews with engineers in the department. My last interview was with the hiring manager and was entirely technical. I received an update 2 weeks after the 4th interview.

    Interview Questions

    • What are co-variates? How do you manage them when creating a machine learning model?   1 Answer
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