Data Analysis Interview Questions

Maryam G. - "At one of my project, I worked on a project where we needed to collect data from different sections of a large factory and deliver it to a third-party company responsible for predictive analytics on product quality and production levels. The challenge was that each department had different data types and structures, and in many cases, direct connections were restricted due to strict security policies. My responsibility was to design and implement a solution that could gather all these heterogene"See full answer

Rishabh R. - "sum of continuous subarray and keep checking if arr[i]==arr[j]. if true increase count;"See full answer

Katherine B. - "If we’re using an A/B test we have a few decision criteria that we can use to measure success. If our primary metric has been shown to be statistically significant (and our confidence interval does not cross 0), and the gaurdrail metrics that we created have not been negatively affected, we should consider shipping. If the our p-value is not significant we can still consider shipping beta if the guardrail metrics have not been negatively affected, and we weigh the opportunity cost of not shippin"See full answer

Archit G. - "line/ trend charts are the simplest method to identify churn "See full answer

George P. - "breakdown the questions from Top- Down or sum up from bottom-ip Identify KPI and North star metrics Identify and analyze cohorts and segments Transform data to actionable insights"See full answer

Sean L. - " debug your code below departments = pd.DataFrame({ 'id': [1, 2, 3, 4, 5], 'name': ['Reporting', 'Engineering', 'Marketing', 'Biz Dev', 'Silly Walks'] }) employees = pd.DataFrame({ 'id': [1, 2, 3, 4, 5, 6], 'first_name': ['John', 'Ava', 'Cailin', 'Mike', 'Ian', 'John'], 'last_name': ['Smith', 'Muffinson', 'Ninson', 'Peterson', 'Peterson', 'Mills'], 'salary': [20000, 10000, 30000, 20000, 80000, 50000], 'department_id': [1, 5, 2, 2, 2, 3] }) projects = p"See full answer

Katherine B. - "We have detailed monitoring and meetings dedicated to discussing the health of the conversion business. When I’ve seen drops in the conversion rate, the first thing I do to diagnose the issue is to work backwards through the conversion funnel. For example, if I see a drop in user adoption rates, I will evaluate if there are any product experiments that could be negatively affecting adoption. Likewise, was there a technical outage that could have caused a drop? Segmentation and cohorting is also"See full answer

Katherine B. - "For ROI for strategic bets, we want to evaluate short term and long-term returns on our investment as well as ensuring we have quantitative and qualitative milestones to measure progress towards the long-term goal. For quantitative evaluation, I would first outline resource investment from upfront capital investment, infrastructure resourcing and clearly capture the opportunity cost of the investment. Then I would set leading success indicators, and business metrics over the timeline of the inv"See full answer

Chao peter Y. - "The question is incomplete --- the code only passes if you return the data frame sorted by BOTH department name AND rank. While in the problem description, it mentions to only rank by department name: "The results should be ordered by department name." Not a big difference I know, but students shouldn't need to look into the solution to get the necessary knowledge to answer the question."See full answer