In this era of big data, the position of data scientists is gaining a lot of popularity. Companies are realizing the need for data analysis to get a better insight into their official data. However, due to lack of any specific vocational course for data scientists, those who are seeking to work for the position are left in confusion. To clear the dilemma we thought of creating this blog post.
Companies are demanding more and more data scientists and there is a serious lack of qualified professional. Even when there is a handsome salary associated with the job, employers are not able to find the right candidate. In the US itself, the average salary of data scientists has been recorded as $123,000, which is a whopping amount.
The rage of data is going to stay for a while so if you are planning to shift your career, this is the time. But, at first, let’s take look at what is data science.
What is Data Science?
Data Science is a multi-level field that brings in use scientific processes an algorithm to extract knowledge and insight from stacks of data. In layman language, data science is all about finding the important aspects of data. It enables companies to learn behavior, trends, and inferences of the mass, allowing them to make important decisions and bring required changes in the on-going processes. Whether you are just beginning your career or want to shift to data scientist, you will need to acquire certain skills; we have mentioned most of them here:
Programming will be the first and most important skill towards achieving a data scientist post. Some of the language you must know for the same are:
- R: R is an analytic tool generally preferred by data scientists. Those wanting to have a smooth journey in the profession should learn R for sure. 53% of the data scientists know Python and R, and of course, they are one to excel in complex situations.
- SQL: In the data industry, SQL always had its firm place and it will continue to be. Learning the language will help you in data extraction, management, and findings. You will be expected to write complex queries in SQL related to insertion, manipulation, and a lot more. However, this is one of the easy ones to learn and is included in some of the school courses too. If you want to take an extensive knowledge of it, try joining an institution.
- Python: Although both R and Python are the basics of a data scientist’s job, you should focus more on Python. This specific language is moving fast with data-driven solutions. Its ease of use and flexibility makes it more popular. There are Python certifications you can attain, which will help you in getting the desired job.
Some other popular languages among data scientists are MATLAB, JAVA, and C++, their need however varies. Most of these are learned in the early phase of the career or depending on what degree you have. For e.g. software engineers know languages like C++ and JAVA.
- Understanding of Statistics
Statistics are vital for every company and if you are going to be part of a data-driven company it’s a must. Your clients will be making important decisions based on your statics evaluation.
Descriptive and Inferential Statistics are the basic Requirement of data science. You will be needed to explain complex theorems in layman language, which requires the basics of statistics. Try to gain enough knowledge about static estimator and distributors.
- Machine Learning
Machine learning is gaining recognition all over data-driven businesses. As a professional, if you are able to make machines that can analyze and make decisions, the chances of risks will minimize further.
Gain a comprehensive knowledge of both supervised and unsupervised algorithms. Although most of these algorithms can be implemented using R and Python libraries, you should know a little about machine learning as well. Stakeholders will be depending on your expertise to analyze and experiment with their data.
- Data Visualization
As a data scientist, you will have to report different statistics and behaviors of the data for which you need to know the data visualization software. Presenting only numbers can be confusing, so take help of some elaborative software. Try to understand the basics and principles behind the visualization as it will help you in decoding your message well.
Some of the famous ones we found are Matplotlib, ggplot, or d3.js. Practice these tools before you go for an interview.
- Software knowledge
You might also want to know a little of the software you will be working on. Being comfortable with the interface allows you to better focus on your job.
- Business knowledge
We can’t say that it’s the most important skill as a beginner, but as you grow the knowledge of your domain counts. Take notice of the trends and terminology. Invest time in knowing your domain more and more, it will add to value for sure.
Most companies demand 2 years of experience, but you should not hesitate as a freshener. Go for it as only 36% of the job is field by experienced professionals. And, if you are an analyst or have worked in any profession closed to data science, getting the job will be easier.
No matter what field you are working in, communication always plays an important role. If you like to be known as a data scientist, start focusing on your communications. There will be jobs like recommending and translating statically output, analytical solutions, and different charts, all of them demanding a great communication skill. It has also been noticed that those with better communication skills quickly make it to the higher level of organization hierarchy.
Even though the pay scale is high, the world of a data scientist is not that different from the other professions. The basics here are all the same as in any other profession. Those with excellent team skills will always be favored as the company can’t run alone. You will have to work with your team, in order to achieve something. Those who have early work experience will have its knowledge, but fresher will need to work on it.
There are institute and online courses guiding you towards your new career choices. Do some research, master these skills and you can have a flourishing career as a data scientist.