Nervous for your Data Science / Data Engineering interview? Start here.

Republished from my blog. View the original article on my blog here.

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Data Science, Data Engineering, Business Intelligence, Data Analysis, and other related positions fall at an intersection of coding, databases, statistics, and business/product. This blend of subjects results in an engaging and challenging career. The interviews are similarly engaging and challenging. :)

When I was studying for my data interviews, I noticed there was not one “holy grail”. I was googling, “review SQL fast”, “data science interview questions”, “statistics questions”, “data model interview questions”, and more endlessly. …


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My career is in Data Engineering, I hold a Bachelors of Science in Economics, and until recently I have been a major skeptic of cryptocurrency. I wasn’t an early adopter because I felt there were economic weaknesses that made the investment too risky.

But after the crash, I came across an interesting perspective that changed my skepticism to interest. I wanted to share my change of mind so enthusiasts and skeptics could better understand their counterpart’s point of view.

First Impressions

I first came across Bitcoin circa 2013 when I was scrolling through news articles discussing its relationship to the Silk Road…


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If you are a developer and want to integrate data manipulation or science into your product or starting your journey in data science, here are the Python libraries you need to know.

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Scikit-Learn

The goal of this series is to provide introductions, highlights, and demonstrations of how to use the must-have libraries so you can pick what to explore more in depth.

Scikit-Learn

Scikit-Learn is built on top of NumPy, SciPy, and matplotlib. It contains an extensive collection of ready-to-use Machine Learning algorithms. All the algorithms are well documented and easy to use for all experience levels.

Focus of the Library

This…


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If you are a developer and want to integrate data manipulation or science into your product or starting your journey in data science, here are the Python libraries you need to know.

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Scikit-Learn

The goal of this series is to provide introductions, highlights, and demonstrations of how to use the must-have libraries so you can pick what to explore more in depth.

Matplotlib

This library is the go-to Python visualization package (except for Plotly which is paid)! It allows you to create rich images displaying your data with Python code.

Focus of the Library

This library is extensive, but this article will…


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If you are a developer and want to integrate data manipulation or science into your product or starting your journey in data science, here are the Python libraries you need to know.

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Scikit-Learn

The goal of this series is to provide introductions, highlights, and demonstrations of how to use the must-have libraries so you can pick what to explore more in depth.

pandas

This library is built on top of NumPy, which you may remember from my last article. Pandas takes NumPy’s powerful mathematical array-magic one step further. …


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If you are a developer and want to integrate data manipulation or science into your product or starting your journey in data science, here are the Python libraries you need to know.

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Scikit-Learn

The goal of this series is to provide introductions, highlights, and demonstrations of how to use the must-have libraries so you can pick what to explore more in depth.

NumPy

Just as it is written on NumPy’s website, this library is fundamental for scientific computing in Python. It includes powerful manipulation and mathematical functionality at super fast speeds.

Focus of the Library

This library is all about the multidimensional…


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Do you ever find yourself in a situation where you need to get information out of a website that conveniently doesn’t have an export option?

This happened to a client of mine who desperately needed lists of email addresses from a platform that did not allow you to export your own data and hid the data behind a series of UI hurdles. This client was about to pay out the nose for a data-entry worker to copy each email out by hand. Luckily, she remembered that web scraping is the way of the future and happens to be one of…


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Have you ever heard the phrase, “it’s not the idea, it’s the people”? Every startup needs top talent to survive — especially top developers. But how do you find them? Interviews of course! I’ve interviewed multiple rounds of people to join an intensive coding community. We are looking for people that we can place into full-time developer positions at the end.

It is easy enough to find tough coding questions to test interviewees’ technical skills, but what about questions to determine characteristics that are hard to measure? Here are a list of questions to help you find those key people…

Lauren Glass

Engineer | Entrepreneur | Tel Aviv

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