Linkedin – Top Paying Jobs Report for 2020 (Data Scientist #3 with 37% growth)
Linkedin – Top Paying Jobs Report for 2019
Linkedin recently came out with their list of “Most Promising Jobs of 2019“. At the top of the list was “Data Scientist”. When we compare the Linkedin list to the prior year list for 2018, Data Scientist was #9. That’s a move UP of 8 spots!
A Data Scientist is a person who “uses scientific methods, processes, and algorithms to extract knowledge and insights from both structured data (like spreadsheets) and unstructured data (like unorganized text)”. (source: Wikipedia)
Source: Instagram @datasciencecampus
The reason there is such a huge demand for Data Scientists is that there is a huge amount of data being generated. According to an article in Forbes Magazine in May of 2018, entitled, “How Much Data do we Create Every Day? The Mind Blowing Stats everyone should read“, there are 2.5 Quintillion Bytes of Data being generated EVERY DAY!
2,500,000,000,000,000,000 Bytes of Data!!!
With the advent of the Internet of Things and high-speed data communications, almost every electronic device on the planet is creating data and it is being stored in the cloud.
Corporations want to make use of this data and generate revenue from it. They want to see what insights they can gain to take cost out of their processes or to generate new revenue streams from it. Data, therefore, represents a strategic advantage to companies and if they don’t take advantage of it, someone else will.
Data Scientists are on the front line of generating these insights and that is why corporations are willing to pay a premium for their skills. There are also limits on how much data a single data scientist can analyze even with the fastest computers and fastest software. So corporations need a lot of Data Scientists (hence the 56% growth rate to 8,000 Jobs in the Linkedin Jobs Data bank).
Machine Learning, a branch of Artificial Intelligence, is another growth area and that is helping take the load off of Data Scientists, as software is used to discover insights; but, the volume of data will just continue to grow as only half the earth’s population is currently connected to the Internet. There is no end in sight for the demand for Data Scientists in the near future. See other interesting facts about the Internet in this article, “100+ Internet Stats & Figures for 2019“.
To see the growth in demand for this profession, the table below shows the comparison between 2018 and 2019:
Rank | 2018 | 2019 |
---|---|---|
1 | Engagement Lead | Data Scientist * |
2 | Software Engineering Manager | Site Reliability Engineer |
3 | Customer Success Manager | Enterprise Account Executive |
4 | Solutions Architect | Product Designer |
5 | Sales Director | Product Owner |
6 | Engineering Manager | Customer Success Manager |
7 | Program Manager | Engagement Manager |
8 | Product Manager | Solutions Architect |
9 | Data Scientist * | Information Technology Lead |
10 | Enterprise Account Manager | Scrum Master |
Data Science (and Python) are Hot!
We have known that Data Science and the most popular language used in Data Science known as Python have been hot skills. There was a fantastic article in October of 2018 on this subject that I shared on Linkedin entitled, “The Most In-Demand Skills for Data Scientists“. I highlighted these two charts in that article:The number of Job Listings on Linkedin for “Data Scientist” totaled over 8,000. And as noted in the first article, this represented a year over year growth of over 4,000 (56% growth).
Learn Python
What programming language should you learn to become a Data Scientist? Python is #1. In the courses below, you will find FREE courses that teach both of these programming languages. I would also recommend learning Jupyter Notebook.
From their website, they state that “The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.” The Jupyter Notebook is an easy way to test out live code and apply what you have learned.
BONUS: Earn the FREE Applied Data Science with Python Badge in just 23 hours includes these 3 courses and 4 badges:
- Python for Data Science (5 hours) – This free Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you’ll be ready to create your first Python scripts on your own!
- Data Analysis with Python (8 hours) – In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn! You will learn how to perform data analytics in Python using these popular Python libraries and you will do it using hands-on labs using real Python tools like Jupyter notebook in JupyterLab.
- Data Visualization for Python (10 hours) – Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. It is a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this Data Visualization with Python course, you’ll learn how to create interesting graphics and charts and customize them to make them more effective and more pleasing to your audience.
You might also like to read:
- How to get a Data Science Job
- Master Python through Learning Real World Applications
- Simple Learning Exercises using Python
- Soft Skills for Success
- Machine Learning in 8 Minutes
A Dozen FREE Courses with Digital Badges for you:
CLOUD (5):
- Bluemix Essentials (4 hours)
- Docker Essentials: Extend your app with containers (3 hours)
- Getting Started with Kubernetes (2.5 hours)
- IBM Cloud Garage Explorer (1.5 hours)
- IBM Garage Method Advocate (3 hours)
DATA SCIENCE (7):
- Big Data 101 (3 hours)
- Data Science for Business – Level 1 (1.5 hours-5 hours)
- Data Science Foundations (3 hours)
- Node-Red: Basics to Bots (4 hours)
- Hadoop Foundations Level 1 (5 hours)
- Python 101 for Data Science (5 hours)
- Data Analysis with Python (8 hours)
BONUS COURSES (2) :
Soft Skills are important too!
Also highlighted in the report are the need for soft skills. What are soft skills? In my blog post, “Soft Skills for Success“, I wrote that soft skills are necessary in order to effectively communicate and connect with other humans.
Soft Skills include skills like Creativity, Persuasion, Adaptability, and Collaboration. If you don’t get along with others and you aren’t able to communicate your ideas, you will not be successful in any job. You could be the best Data Scientist in the world, and glean amazing insights from data, but if you don’t know how to persuade others about those insights, then they won’t have an impact.
Most scientists know that it can take upwards of 20 years to get the greater scientific community to adopt a new discovery. The rigor and scrutiny that new scientific findings go through is not for the faint of heart. Unless the Scientist has true GRIT, he won’t be able to withstand the pressure and many give up along the way.
Having the soft skills to adapt and persuade and present in these times of great scrutiny are invaluable in the Data Scientists skills tool belt.
Infographic – Feel Free to Share
Lastly, here is an infographic that I created highlighting not only the most promising jobs but also the key soft skills and hard skills that you will need to learn.
We have also created a community dedicated to helping others learn key skills like Data Science and Python. If you join, you will meet others in the community who are Data Scientists and will help answer your questions. Details on joining the community are given below the infographic.
And for those that would like to create an infographic like the one I created below, I did this in about 2 hours using an online tool called Canva. They have infographic templates that you can use and make an infographic super easy to create.
Join a community of like-minded people who want to make time for learning and encourage others to reach their goals.
Upskill Create is all about creating a lifestyle of continuous learning and then applying what you have learned to secure your future and create a life you love.
We offer an engaging private community of fellow “Upskillers” to provide an environment where we can learn, collaborate and encourage each other in this journey. You can request an invitation to join this FREE community at the bottom of this post.
I hope you will join me,
YN
Exploratory data analysis is one of the most important parts of any machine learning workflow and Natural Language Processing is no different. But which tools you should choose to explore and visualize text data efficiently?
In this article, we will discuss and implement nearly all the major techniques that you can use to understand your text data and give you a complete(ish) tour into Python tools that get the job done.
Good information you shared. keep posting.
data science courses
Really Nice Information It’s Very Helpful All courses Checkout Here.
data science course in malaysia
This is also a very good post which I really enjoyed reading. It is not every day that I have the possibility to see something like this..
data scientist course in pune
I am reading your post from the beginning, it was so interesting to read & I feel thanks to you for posting such a good blog, keep updates regularly.I want to share about
machine learning training in aurangabad
This post is very simple to read and appreciate without leaving any details out. Great work!
data scientist course in malaysia
Interesting post. I Have Been wondering about this issue, so thanks for posting. Pretty cool post.It ‘s really very nice and Useful post.Thanks
full stack web development course in malaysia
This is a really good article. Clear and consises.