Frequently Asked Questions (FAQ)

Do you have a question about data science? Or about Just into Data?
Check out the FAQ below. This page will be updated continuously.

We are here to help you become great at data science.
If you still have questions and need help, you can contact us through the Contact Form in Let’s Connect page.

General Questions

Instead of giving a lengthy definition, we'll give you a moment to imagine:

  • you can explore the world based on data (analysis) to discover the insights.
  • you can impact the world by using advanced technologies, machine learning algorithms.
  • you have a good salary job that you are passionate about.

But to get there, you'll need to:

  • learn statistics theories and complicated machine learning techniques.
  • be comfortable with some coding.
  • deal with messy data.

That is an overview of data science!


Do you know that Netflix relies on machine learning recommendation algorithms to provide you personalized shows to watch?

Do you know that iPhones use deep learning neural networks for face recognition?

Do you know that Google relies heavily on data science to determine the most relevant results to our queries?


Yes, data science exists everywhere in our lives. We are enjoying the convenience it brings every day.

That's why it's an essential and in-demand skill to learn, for everyone!


We created Just into Data blog to help you get into data science. Sign up for our newsletter for regular high quality articles.

This is the most popular question about data science!

It largely depends on the industries/locations/experience.

To give some ideas, the average salary within the US for Data Analyst is $62K/year, while for Data Scientist is $113K/year, according to Glassdoor.

There is no doubt that data science does provide well-paid careers in general.

Yes, we already discovered that data science jobs provide above average salaries in the previous question. But is it a good career overall?


According to Glassdoor, Data Scientist has been the best job in the US for the past 4 years. It has a high job satisfaction score of 4.3/5 in 2019.


According to Indeed, data science postings have rocketed 256% since December 2013. While postings have surged, job searches for data science positions have grown more slowly. So it is highly in-demand.


With skills of data science, you can work in various fields such as:

  • marketing
  • finance
  • healthcare
  • robotics

You can be doing things such as:

  • analytics
  • prediction
  • classification
  • recommendation
  • Natural Language Processing (NLP)

There are also various data science career paths.

You can be a reporting analyst, a data analyst, or a data scientist. They all require different strengths/skill sets.

So there are many career paths to choose from, you will not get bored.

Often data scientists use their technical skills to extract insights from data and bring it to action for businesses.

Depends on the organizations, the typical tasks include:

  • Understanding the business problem and propose data science solution
  • Collecting datasets from disparate sources
  • Cleaning and validating the data
  • Researching and applying data mining skills, models, algorithms on the data
  • Summarizing and communicating findings to other business partners

A typical day of data scientists would involve:

  • Working on the computer
  • Sharing ideas within meetings with the rest of the team or other business partners

Further Readings:

Data Cleaning Techniques in Python: the Ultimate Guide and How to use Python Seaborn for Exploratory Data Analysis to get a better idea of what data scientists have to do before the exciting modeling parts.

This, again, largely depends on the industries/career paths.

But we summarized answers to these questions based on Indeed job postings for data scientists.
Further Reading: What are the In-Demand Skills for Data Scientists

In summary, the most in-demand skills required for data scientists are:

  • Python
  • SQL
  • Machine Learning

We strongly suggest starting your data science journey by learning Python first.

It is a free and powerful program that's capable of many different tasks.

Also, it is better to start with technical skills than theoretical knowledge.

You'll be able to apply the machine learning/statistics techniques with Python when you are learning about them later. That makes it more fun and understandable!
Further Reading: How to Install/Setup Python and Prep for Data Science NOW

We are planning on launching a mini-course breaking into data science with Python in the near future.

Stay tuned by signing up for our newsletter!

It depends on the person. Everyone has his or her unique strengths.

But remember, nothing is really easy to learn. But anyone who's determined has a higher chance of succeeding.


We are planning on launching a mini-course breaking into data science with Python in the near future.

Stay tuned by signing up for our newsletter!

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