Uber Data Scientist Mock Interview | Interview Coach (Ex-Google)

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====== ⭐ Details ======
Dan, a former data scientist at Google, conducts a mock interview for Uber's data scientist role. The interview is based on the technical screen which typically consists of SQL and product sense questions.
As an interview coach, Dan has helped several clients land their dream jobs as IC and managerial DS roles at top companies such as Google, Meta, Amazon and such.
Got questions? Message him at [e-mail]
Make sure to check out 👉 datainterview.com/
====== ⏱️ Timestamps ======
00:00 Intro
01:45 SQL
16:23 Product Sense
====== 📚 Other Useful Contents ======
1. Principles and Frameworks of Product Metrics | KZbin Case Study
Link: / principles-and-framewo...
2. How to Crack the Data Scientist Case Interview
Link: / crack-the-data-scienti...
3. How to Crack the Amazon Data Scientist Interview
Link: / crack-the-amazon-data-...
====== Connect ======
📗 LinkedIn - / danleedata
📘 Medium - / datainterview

[@anggipermanaharianja6122]

The SQL question is really a good one, good to see more question sample like this

[@DataInterview]

More coming!

[@Aidan_Au]

I can't believe that Dan just put this priceless content out for free! Imagine how much more valuable his coaching would even be! Your student Matt in Meta said that SQL and Case Study are usually the technical screen. I'll def get good at those before applying.

[@DataInterview]

Thanks Aidan as always :) -- Dan

[@trangpham6025]

shouldn't the cancellation rate in the first SQL question be sum(number_of_orders) with status_of_order = Cancelled / sum(number_of_orders)?

[@DataInterview]

The short cut is to just use an indicator function on the cancellation and take the average of that which gives you proportion

[@ozmundsedler]

@@DataInterview but you don't take into the account number of orders in this case, so the proportion won't be correct.

[@huanchenli4137]

group by man@@ozmundsedler

[@firesongs]

Really great case study q and analysis

[@hemantsharma7986]

This is great bro👏

[@liverpooler1997]

I think the candidate was nervous and spike before thinking many times in the product case. Maybe if she had a couple minutes to compose her thoughts, she coulda done better.

[@rihaansatia2812]

shouldnt ther be a group by at the very end?

[@user-wb7vz8fx9k]

Hey Dan, first thanks for the great content! I wanted to ask if the CTE is really necessary here, because in my head we could do it with one query as follows: SELECT service_name, AVG(CASE WHEN status_of_order = 'cancelled' THEN 1 ELSE 0 END) as cancel_rate, AVG(monetary_value) AS avg_mont, MAX(number_of_orders) as max_count FROM RideStatus GROUP BY service_name ORDER BY cancel_rate DESC LIMIT 3;

[@akshayiithyd]

This will only work if the cancel_rates are distinct

[@asdfgg7104]

thanks

[@user-vg9ms2hw1w]

Hello, This is a very good mock interview. What level of data science interview is this? Is this a similar interview from L3 to L5 Data Scientist ?

[@DataInterview]

L4 plus

[@yemunnsoe8450]

She's not really paying attention to the interviewer and is eager to share her thoughts and answers

[@songsong2334]

Thanks Dan!!!! Great question!! For the SQL question, my thoughts will be the following. ##Find out 3 service names with the highest cancel rate. With sn as( SELECT service_name from( SELECT DENSE_RANK()OVER(ORDER BY ROUND(SUM(CASE WHEN status_of_order ='cancelled' then 1 else 0 end)*100.0/Count(*),2), service_name) rnk GROUP BY service_name) sub where rank

[@DataInterview]

I would say, for redability, decouble the rank and case part into two separate subqueries. In the last part, you are missing GROUP BY.

[@jojushaji3010]

Can we use python group by function

[@DataInterview]

If the interviewer asks for it in Python, then yes.