The Google Data Analyst Interview

Intro

Like many of the Tech giants, Google, leverages data to the fullest extent in all parts of its business. This provides many ongoing opportunities for those looking to get hired into an Analyst role at Google! This blog post will take you through the role, required skills, the interview process, a few example questions, and some tips to help you start preparing for your interview.

The Role

Analysts are embedded throughout Google, meaning there are many opportunities and analytics roles available. Below are just a few types of analysts that Google hires for:

  • Financial Analysts - Folks in this role ensure that Google is spending and making money for the business according to plan. Financial Analysts can be aligned to a product area (think Youtube, Google Playstore, Google Cloud) or can be a part of the core finance function.
  • People Operations Analysts - These analysts help monitor and track activity across HR, spanning from Googler’s compensation to analyzing work habits to making sure Google has the right amount of recruiters in order to hit their hiring targets across the business.
  • Product Analysts - These analysts work on understanding how users interact with the different Google products and provide analysis to help improve the products, working closely with Engineering.
  • Trust and Safety Analyst - These analysts help ensure Google's content-focused products (such as Ads) have content that are compliant with Google’s policies. These teams work heavily with Engineering to build/improve machine learning models centered around flagging content.

Required Skills

An average Google analyst typically has 3-4 years of experience in a quantitative role. However, there are definitely instances on both ends of the spectrum, some with 15 years. Other qualifications for Google Analysts include:

  • Bachelor’s or higher in a technical program such as Mathematics, Statistics, Computer Science, Physics, Engineering, Operations Research, Economics, Engineering
  • Experience with SQL
  • Experience with relational databases and business intelligence tools
  • Basic experience with scripting languages (e.g. Python, Java)
  • Experience with stats software such as Numpy/Pandas/Scikit Learn or R (Colab Notebooks are a great way to practice this skill)
  • Experience working with cross-functional teams

These skills vary from role to role, so be sure to read into the specifics for a particular role.

Interview Process

The typical interview process at Google follows the steps below:

  • Initial screening by a recruiter (~30 minutes). This is more of a formality to ensure the candidate fits the criteria for the role. The recruiter will ask about past experiences, your interests, and will provide you more details about the role.

  • Initial phone interview with a member of the current team (45 minutes). This interview will cover past experiences, but with more of a focus on technical skills and problem solving ability. It’s important to use stories / past experiences that highlight your technical expertise here.

  • Potential case study (24-48 hours to complete). Depending on the role you are applying for, you might have a take home case study. Typically, this case study will be reviewed by a member of the team, and provided you pass this step you may then have to discuss it during your onsite interviews.

  • Onsite interview. Here you'll run through a slate of interviews with the current team (it's likely one of the interviews will be with the hiring manager) and cross-functional team members. These interviews will take about 1/2 a day - interviewing with 3-4 people for about 45 minutes each. These interviews can be structured in many different ways depending on what team you’re interviewing for, but generally onsite interviews focus on 4 main areas:

  • General Cognitive Ability: This area is graded based on general problem solving and critical thinking, along with the ability to communicate your line of thinking.

  • Leadership: This will focus on how you’re able to help lead a group to a positive outcome, either with or without direct leadership authority.

  • Role-related knowledge. Here you'll have a more technical interview, likely covering SQL along with your technical approach to hypothetical problems.

  • Googleyness: “Googleyness” is a set of qualities like fun, intellectual humility, conscientiousness, and a record of having done interesting things. Be yourself and if you have any side projects outside of your core “experience” this will help you do well in this area.

Example Google Data Analyst interview questions

  • If you are the owner of a flower shop, how would you target your customers online? (Who? When? Where? How?)
  • How would you measure customer check out rates? How would you go about doing this?
  • Name a Google product you use. What would you change about it and how would you improve it?
  • Give me an example of a project you’ve led. What was the result? Which difficulties did you meet?
  • How would you measure how much a given user liked a video?
  • Explain confidence intervals to someone with no statistics background.

Tips to help prepare for your interview

  • Brush up on your SQL along with any other technical skills listed in the requirements.

  • Come prepared with 6-7 stories based on past experience that cover the following:

  • A time you disagree with a team member, how did you deal with this?

  • A time where a client had unreasonable demands, how did you respond?

  • A time where you took on a leadership role formally or informally.

  • A time where you took a risk, what made the risk notable?

  • A time where you worked on a particularly difficult project. What made the project difficult?

  • An example of a time you were leading a group and it wasn’t going well, how did you turn it around?

  • Ensure that you have spare copies of your resume.

  • Use the STAR Method when drawing from past experience.

  • Relax and be yourself! Many folks interview at big tech companies multiple times before landing the role, so don't sweat it if you don't land a role on the first try -- you'll gain great experience either way and be better prepared for future interviews.