Data scientist was coined as one of the best tech jobs in America consecutively for four years, according to Glassdoor. Not to forget it is also one of America’s highest paying job. Is it worth taking up a career in data science? It definitely is, in fact, it is one of the best career choices one can make today.

In a world that is filled with technology enhancement and digital space, organizations are seen dealing with Zetta and yottabytes of structured and unstructured data daily. Well, only a few people are trained and skilled to perform tasks that help the organization gain benefit from these data, and they are called as, “data scientist.” Most industries these days are in a need for expert professionals skilled in data science.

Moving further, data science knowledge is created based on data. It is a detailed study of data that is collected from the organizations’ repository. Being a data scientist, one needs to obtain meaningful insights from the data collected. The raw data that is collected is cleaned, structured and analyzed using various tools and technologies. Companies are flooded with huge amounts of data, and it is crucial that one knows what to do with this silo of data and how one can utilize them.

Here are the data scientist skills you need to master today:

Statistics and Mathematics: A data scientists should be like a software engineer who is good at statistics and better than a statistician in software engineering. The basic thing you need to follow is to have that balance maintained. One can start off easily by learning both descriptive and inferential statistics. Descriptive statistic involves more into characterizing a sample of reality and includes measure as center such as mean median, shape, dispersion, etc. On the other hand, inferential statistics is more towards making conclusion regarding population-based sample data.

Coding: To become a data scientist you need to know how to code, you must know the language by which your data can communicate. Since you’re from an IT field learning another new language shouldn’t be much of a hassle. A good coder cannot always be good data scientists but good data scientists should be a good coder. During your career in data science, you will write a bunch of scripts, automation, and programs. R and Python are some of the languages you’re required to know as a data scientist.

Databases: You might be aware that there is a huge amount of data that is being generated every minute, every second, which is why most of the organizations use database management systems such as NoSQL for analyzing and storing data. Having good knowledge about MongoDB is important to have a secure future as a Data Scientist.

Machine Learning and Deep Learning: You need to understand different types of Machine Learning techniques such as Supervised, Unsupervised and Reinforcement Learning. It would be an added advantage if you have knowledge in Neural Networks for deep learning.

Data Wrangling and Data Munging: You need to know the process of how the data is imported, transferred, loaded and processed. Data Munging is basically the process of transforming data from one “raw” data form to another form with an intent to make it more appropriate and valuable.

Data Visualization: You need to have good hands on visualization tools such as Tableau, Datawrapper, and Kibana, etc. only then you’ll be able to demonstrate the information and data.

Communication Skills: At the beginning of every Data Scientist’s journey I am quite sure that no one was good at presenting their findings. This overcomplicates things, I know this from my personal experience that is why it is always advisable to practice your findings. Practice will eventually make you learn and gain experience with time.

Get hands-on Data Science Projects: Once you have gained enough confidence in the theoretical aspect, you need to work on the practical aspect as well. You will find a huge number of Data sets projects online, this will help you understand data analysis better. Try experimenting with things and projects, this will eventually help you become better day by day.

Be Observant: You might know that Data Scientist will be one member of a team and when you’re working at such an environment, you’re required to have very good observation qualities. Being a good observer will help you gain knowledge and will help you develop different skills that will make your work more efficient.

Get involved in competitive projects: Being a Data Scientist you should know where your skills lie and how competitive it is or will be working with other Data Scientists. Working with real-world problems is the only way you can know what others can be capable of, plus you will also learn from them.

Having said these are the data scientist skills that will help you become a data scientist sooner. However, although it may seem like a walk in a park, these skills do not come overnight. One needs to delve deeper in search of resources and firms that offer these skills. A simple way to start a career in data science is by taking up credible certifications and kick start your dream journey.