Data Scientist | April 2020

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jacquelinech3n49April 5, 2021, 01:12 AM
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Company: Airtable

Position: Data Scientist

Location: San Francisco Bay Area, CA

Level: nan

Outcome: NA

How was the interview process? What was it like?

I felt confident in the interview and think I did well in answering the interviewer's questions. I think what surprised me the most was how simple / easy his technical questions were. My advice would be to practice technical questions over and over again until you understand the syntax and its usage so that you can answer those curve ball questions.

What technical questions were asked?

SQL / Pandas, Statistics & AB Testing, Modeling and ML knowledge

What was one of your solutions?

1. The union function appends the datasets (and in order to use that function, the datasets must have the same number of columns). Furthermore, a union all can be used if you don't mind having duplicate data. Otherwise, if you do not want duplicate data, you can simply use the union function. 2. The join statement merges two datasets, if both datasets share the same primary key (since you would join the two datasets via the primary key). You would use the join if you wanted to merge the dataset together (i.e. combining data vertically), whereas you would use the union function if you wanted to append data (i.e. combing data horizontally). 3. A window function allows you to summarize data within a specific group of data (for instance, you can use a window function to get total sales for each sales person by month).

Data Scientist
I
Ichimoku
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Ichimoku
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