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In 2008, Google launched its cloud solution "Google Cloud Platform" (GCP), a suite of cloud computing services that offers excellent Infrastructure-as-a-Service (IaaS) solutions to help businesses scale up.
Today, GCP is used in almost every industry, including manufacturing, retail, finance, healthcare and life sciences, gaming, education, telecommunication, and government. Google Cloud Platform also offers Big Data (Big Query large-scale data warehouse, Dataflow, Cloud Datalab, Cloud Datalab, Data Studio, etc) and AI/machine learning solutions for “ML model development, search, natural language, speech, translation, vision and video intelligence”.
Over the years, Google has spent a fortune developing analytics and cloud-based architecture tools to help businesses grow. Data and data analytics is integral to the company’s core vision, and as such, Google offers work on a scale like no other to incoming data scientists, data analysts, data engineers, and business analysts.
The Product Analyst Role at Google
Generally, a product analyst is one who utilizes market research, data analytics, and business intelligence skills to successfully launch a new product to market. The role is specialized at Google. Product analysts at Google leverage data analytics to find different insights to drive business impacts. They provide “quantitative analysis, market expertise and a strategic perspective to both Google’s internal clients and partners throughout the organization”.
Product analysts at Google generally oversee the complete journey of a product, including its design stage, before launch, and after launch. There are so many questions surrounding a product journey (from design to market), and product analysts help answer real questions like “What are we trying to make happen?”, “How can we prove it quantitatively?”, and “Are we confident in that?”.
Product analysts also work cross-functionally with internal teams, guiding them on product direction, experimentation, and analysis, and with developers, helping them achieve success in their projects.
Like every Google position, the product analyst role requires enterprise-level analytics skills and at least three years of industry experience in quantitative analysis.
Other relevant skills include:
- Bachelor's/Master's in Statistics, Computer Science, Mathematics, Engineering, Data Science, or other quantitative fields.
- Extensive experience with statistical packages including R, SAS, Stata, MATLAB, etc.
- Deep experience writing SQL queries, extracting large data, and designing ETL flows.
- Experience in developing models, methods/approaches (including Time series forecasting, econometrics, causal Inference, and classification methods), and the ability to translate analysis results into business recommendations.
- Three years experience working with engineers and product managers, especially around providing product-centric insights.
Product Analyst Teams at Google
While product analyst roles sometimes overlap with those of business analysts, product analysts rely heavily on quantitative analysis, rather than focusing on the business impact of product design. They work within teams and cross-functionally with others to achieve business goals.
As a large company with many teams working on product development and design around a lot of different products and features, Google offers a unique scale that is very global, making even your tiniest efforts significantly impactful. Depending on the assigned team, specific roles may differ. Below are some of the product analyst teams at Google and their specific roles:
- Data Science Team: Product analysts on this team conduct analysis for business recommendations, develop and automate reports, and iteratively build and prototype dashboards to provide insights at scale. They also present findings to multi-level stakeholders and collaborate cross-functionally with stakeholders to formulate and complete full cycle analyses.
- Developer Console: Roles include partnering with Engineering and Product Management teams in Developer Console to understand their business needs through end-to-end analysis, including gathering and analyzing data and ongoing scaled deliverables, and delivering effective presentations and recommendations to multiple levels of leadership. The position also involves developing and automating reports, and prototyping dashboards to provide actionable insights at scale.
- Youtube Data Science Team: Roles include guiding the team on product direction through rigorous experimentation and analysis, and working closely with the engineering team to achieve a successful product development journey.
The Interview Process
The product analyst interview process follows Google’s standard hiring process. The interview process starts with a recruiter reaching out to you via email to gauge your interest. The next step is completing a ten-question survey about your past projects and role-related skills. After this, an initial interview with a product analyst will be scheduled via phone call or Google Hangouts. The final stage is the onsite interview, consisting of four interview rounds with product analysts from the same team.
The Google product analyst initial screen is exploratory. It is a 45 minute phone or Google Hangouts interview with a Product Analyst (PA); questions can range from past project experience type questions to light technical type questions.
Sample Question: How would you explain a 95% confidence interval to a non-technical person?
Here are 15+ product analyst interview questions to practice before your next interview.
This is the last stage of the Google product analyst interview step. This interview consists of four back-to-back interview rounds with product analysts (within the same team or outside the teams) and a lunch break in between.
Standard Google product analyst onsite interview questions can comprise modeling, metric definition, SQL, and standard statistics problems. Questions can also range from hypothetical to case-based and real-life scenarios. There are also behavioral, product sense, and culture-fit questions on these interviews. You can expect questions with a format like, “How would you..”, and “Tell me about a time you..”
Note: It is important that you talk through your solution in the interview, and it also helps to use past projects you've worked on to explain your answers and choices.
Notes and Tips
Google is a product-based tech company, and product analysts at Google are expected to leverage data and advanced analytics methods to drive product growth. The Google product analyst interview aims to assess candidates’ ability to perform job duties to drive the success of Google’s products.
Google uses standardized questions that are tailored specifically to roles in all its interview processes. Solving Google product analyst SQL and Python questions on Interview Query will go a long way to help you succeed in your interview.
Remember, the Google product analyst interview will also test a combination of statistical and data analytics concepts, as well as product-sense and business analytics concepts. Brush up your knowledge of basic statistics and probability, predictive modelling, metrics definitions, and SQL (including ranks, joins, etc,).
It is also worthy of note that Google is looking at four main standards for all its interview processes, regardless of the roles and department you are applying for. The first is “general cognitive ability”, the second is “role-related knowledge”, the third is “leadership skills”, and the last is your “Googlyness”.
Google employs rigorous post-interview hiring processes that include team matching and putting together offers. This is done by a team of highly-qualified and non-biased Googlers, “the Hiring Committee”, who are experts in the roles/jobs and have never met any of the applicants before. After the verdict of the hiring committee, they send out a recommendation to senior management for final review before an offer is extended.
Google Product Analyst Interview Questions
- Given a hypothetical situation, how would you create a model to predict this metric?
- How would you handle class imbalance, etc.? How would you use this model in a business context?
- How do you use rank() to get id(s) with the highest value?
- Is sorting one column or sorting concurrently pieces of that column faster?
- How would you test a new product?
- How would you explain AdSense to a grandmother?