Communication Skills and Clean Data are a Data Scientist's Best Friends

Alejandra Budar is an Associate Data Scientist with the Economic Graph Team at LinkedIn. The team she is a part of analyzes market trends and forecasts and translates that data into workforce recommendations.

In the interview with Promotable.io founder Aaron Filous and Course Instructor Scott Adams, PhD, Alejandra shares vital job search and interpersonal skills that are helpful to every data scientist.

She also offers her take on the differences between a data scientist and data analyst, and how a a data scientist can take form of a machine learning engineer from time to time.

Before Alejandra jumped into data science, she was preparing for a career in the healthcare industry. The gap year she took allowed her to connect with her interests, and data science ultimately won out.

JUMP TO
02:28 Meet Alejandra, Data Scientist at LinkedIn.
05:09 Why do you prefer SQL over other languages?
06:59 What's your day-to-day look like in your role as a LinkedIn Data Scientist?
08:40 What drove you to data?
10:33 The importance of knowing the difference between a data scientist and data analyst.
11:33 What did you learn on the job that you didn't get in school?
12:27 Writing clean code for others to read is an underrated skill.
14:40 How did you prepare for your data science interviews?
15:41 Critical thinking is an important skill for a data scientist.
16:56 Communication tips a data scientist can use in a team.
24:42 How is machine learning used in data science?
26:51 How much SQL knowledge do you need?
28:09 How important is business knowledge to your role?
30:01 What is your data visualization of choice as a data scientist?
36:41 What was the most difficult part of your data science job interview?
38:38 Who are the stakeholders for a data scientist?

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