Lyft/Uber Metric Interview Question and Answer: Tips for Data Science Interview Success!

Summary

In this video, Emma revisits the topic of metric interviews, focusing on a real question from Lyft: investigating an increase in average ETA by three minutes. She outlines a systematic approach to diagnosing the problem, emphasizing the importance of clarity, time factor analysis, and segmentation by user demographics or platform. Emma then role-plays an interview, demonstrating how to apply the framework interactively with an interviewer. The video aims to equip viewers with strategies for tackling similar metric questions in their interviews.

Takeaways

• 📈 The video is a guide for tackling metric interview questions, specifically using a real question from Lyft.
• 🔍 The presented question involves diagnosing why the average ETA has increased by three minutes on a dashboard.
• 📝 Emma provides a six-step framework for approaching metric problem diagnosis, which was previously covered in another video.
• 🤔 The framework encourages a systematic approach, starting with understanding the metric and scenario, then investigating from various angles.
• 🕒 The steps include checking for outliers, time factors, changes in algorithms, and data collection processes.
• 📊 It's important to segment the metric by user demographics and behavior to isolate issues and decompose the metric if necessary.
• 📉 Emma emphasizes the need for a systematic approach to convince the interviewer of the candidate's organizational skills.
• 🗣️ Interaction with the interviewer is key, as it helps to confirm the approach and allows for direction based on feedback.
• 🧐 The interviewee should be prepared to adjust their investigation based on the interviewer's prompts and the evolving discussion.
• 🌐 The script suggests further segmentation by region and platform to narrow down the issue if it's not a company-wide problem.
• 🔑 The importance of summarizing the approach is highlighted to show the interviewer a clear and structured method of problem-solving.
• 💻 Emma offers to help viewers with difficult interview questions by providing guidance and potentially creating videos for common queries.

Q & A

What is the main focus of the video by Emma?

The main focus of the video is to provide guidance on how to answer a real metric interview question from Lyft, specifically about investigating an increase in the average ETA by three minutes.

What type of question is being discussed in the video?

The question being discussed is a typical diagnosis of a problem type of question, where the target metric is the average ETA.

What are the six steps provided by Emma for answering metric interview questions?

The six steps are: 1) Clarify the scenario and the metric, 2) Investigate the time factor, 3) Check for changes in algorithms or processes, 4) Segment the metric by user demographic and behavioral features, 5) Decompose the metric, and 6) Summarize the overall approach.

Why is it important to clarify the scenario and the metric at the beginning of the interview?

Clarifying the scenario and the metric is important to ensure a full understanding of the problem and to avoid misunderstandings that could lead to incorrect analysis.

What does Emma suggest doing if there are outliers in the data?

Emma suggests setting a threshold, such as 99.99% of all ETAs, and investigating any extreme values that are much higher than the threshold to determine if they are due to data collection errors or technical issues.

How does Emma approach the investigation if the average ETA increase was sudden?

Emma suggests checking for recent changes in the ETA calculation algorithm, the rider-driver matching algorithm, and the data collection process as potential causes for a sudden increase in average ETA.

What should be done if the average ETA increase is happening progressively?

In the case of a progressive increase, Emma recommends looking at historical trends, comparing ETA against actual time of arrival, and investigating factors such as changes in the number of riders and drivers, or regional and platform-specific issues.

Why is it suggested to segment the metric by different dimensions like region and platform?

Segmenting the metric helps to narrow down the issue to specific regions or platforms, which can provide insights into whether the problem is isolated or widespread and assist in identifying the root cause.

How does Emma emphasize the importance of interaction with the interviewer during a metric interview?

Emma emphasizes the importance of interaction by suggesting that the interviewee should confirm their approach with the interviewer, ensuring that their explanation is clear and robust, and that they are responsive to the interviewer's feedback.

What is the final step Emma suggests in her approach to diagnosing the issue of increasing average ETA?

The final step Emma suggests is summarizing the overall approach, which includes understanding the data, identifying factors affecting the average ETA, and analyzing when and where the change occurred, to show the interviewer a systematic approach to solving the problem.

How does Emma encourage viewers to engage with her content for further help?

Emma encourages viewers to share difficult interview questions they've encountered, promising to provide guidance on how to answer them and potentially creating videos to help with those specific questions.