Will Data Science remains the sexiest job of the 21st century as Harvard Business Review wrote in 2012 – nobody knows. What is obvious, though, is that for the last 3 years the Data Science career wins the first place of the Glassdoor’s ranking for the best job in America. And how it won’t as the job satisfaction score is 4.2 out of 5, the median base salary is 110 000 dollars and there is a huge demand for professionals. Sounds seducing? For sure it does but how can an undergraduate begin on their data career path?

Data Scientist: The Sexiest Job of the 21st Century? http://t.co/kJX1QlMD

— Harvard Biz Review (@HarvardBiz) September 21, 2012

 

Choose the Data Science role for you

If you have landed to the article, probably you are a student of Business Intelligence, Computer Science or you are on your way of finishing a degree in Mathematics, Statistics or Physics. Either that or a passionate data science enthusiast who loves making a sense of information and love turning data into knowledge. In both cases, you need to choose the direction of your efforts of mastering in the role of the Data Science profession.

Source: DataCamp

Role #1 – Data Architect

With the huge amount of data, comes the demand for designing, creating, deploying and managing an organization’s data architecture. This is where the data architect is showing up to create a structure for the data management system which needs to be centralized, constantly maintained, protected.

Role #2 – Data Scientist

As one of the best paying jobs, the Data Scientist job is to collect, analyze, interpret large amounts of data and present it in an understandable way. The Data Scientist’s task is to follow the latest data mining and visualization technologies as well.

Role #3 – Business Analyst

Apart from the mathematical and programming educational background, a person can be a professional in Data Science having more business understanding. As a business analyst, it’s is very important to understand business processes and to act as the bridge between the IT geeks and business stakeholders.

Check out the whole infographic by Analytics Vidhya presenting the key roles in Data Science, their skills and talents.

 The learning journey never ends

After choosing the right role for you, it’s good to start experimenting with data for you to further develop in the field. That’s why you will need to master the fundamentals and to practice more and more using the right instruments and building the necessary skillset.

As a data science enthusiast, you should know that the fundamentals lie in Computer Science, Math and Statistics mixed up with Business knowledge and understanding. There are several learning paths you may take.

Learning Path # 1: Courses

You can start with the theory. Here are some of the best ranked free Data Science Courses for 2014 according to Forbes:

• EdX – Data Science Essentials
• Udacity – Intro to Machine Learning
• KDNuggets – Data Mining Course

Some more like with more practical examples:

• Data Science A-Z™ by Kiril Eremenko
• Data Science foundation courses by IBM

To get used to work as a Data Scientist as it is in reality, you may try coding directly in a Jupyter Notebook where you can write in Python, R or else. Here is a guideline how to start your first Notebook.

Of course, there are many more courses you may start with but remember to be consistent in your learning process.

You can make the switch into a STEM career as a Data Scientist official through obtaining a degree. In this article, you can find some tips on initial funding, grants, and scholarships.

Learning Path #2 – Data Challenges

There is nothing like the hands-on experience with the data. When you start looking into it, you may find the patterns you were searching for. But datasets are difficult to find and especially with detailed explanations. Where to find those challenges with real data to experiment with?

Data Science Challenges may be found at

• Kaggle
• Analytics Vidhya
• Data Science Society platform

What you can do right away is joining a Monthly Challenge which will walk you through the process of solving real-world data case with the help of a mentor. What’s might be a good investment in time is to start learning and collaborating with other data fellows in a live chat. There you may find numerous pieces of advice from first-hand experience how to excel in your future career as a Data Scientist.

After following the guidelines step by step, you can brag around that you are closer to predict the air pollution in the next 24 hours which is the task of the challenge.

Don’t postpone your learning journey!

May the data be with you and good luck!