4 Reasons: Why a career in Data Science is very lucrative

Are you looking for answers to your queries regarding a career in Data Science? Are you confused about Why, How and What of Data Science? This article will address your queries and will talk about the requisites of the field.

Data Science, a major disruptive technology, has become one of the most sought after career choices. The versatility of the revolutionary technology has created humongous opportunities for those who have the required skill set.

What is Data Science?

Before planning a career, one must know what exactly is Data Science. Data Science is the study of data, it is an interdisciplinary field which is an intersection of programming, mathematics and statistics along with the business expertise. This domain is an interesting mix of technology along with human traits like intuition, critical thinking, visualizing and so on. Data Science is being leveraged to extract, analyze, visualize, manage and store data to create valuable insights with the use of scientific methods, processes, algorithms and systems.

Why choose Data Science as a career?

Data Science is not just a job, it is a prominent career and has a huge scope of growth in the future. It is highly in demand and has numerous opportunities for prospective job seekers. Being one of the most sought after careers, Data Science has huge applications across industries like Healthcare, Telecom, Retail, Marketing, Credit Insurance,Travel and many others. MNCs have already started hiring of data scientists in huge numbers. As per a report by IBM, the demand for Data Science job roles will surge by 28% through 2020. So, a career in Data Science is regarded as one of the best career choices in the 21st century.

This domain welcomes everyone who is interested to build Data Science expertise regardless of their backgrounds. Students from fields like Mathematics, Computer Science, Engineering, Social Sciences, Commerce, Business Administration and Physical Sciences can also build a career in Data Science. They will need to have good knowledge of mathematics and statistics to start with.

Also read: 5 Reasons to Build a Career in Data Science https://www.nationalskillsnetwork.in/5-reasons-to-build-a-career-in-data-science/

What are the key skills of a Data Scientist?

While it is possible for just anyone to build expertise in Data Science, the question is how to do so.

If you aspire to become a Data Scientist, you must have certain technical as well as non-technical skill-sets. These skill-sets are prerequisites to building a career in this revolutionary technology and will help in career growth.

Must have technical skill sets for an aspiring Data Scientist

Mathematics and statistics: As a Data Scientist, you will use capital processes, algorithms or systems to get valuable insights and make informed decisions from data. Here good knowledge of mathematics and statistics would help you while making estimation for further analysis. If you wish to build a career in Data Science, you should be familiar with the following topics of

Derivatives and gradients
Step function, Sigmoid function, Logit function
Cost function
Plotting of functions
Minimum and Maximum values of a function
Scalar, vector, matrix and tensor functions

Programming languages: Programming languages are a crucial part of Data Science, they are essential in transforming raw data into actionable insights. While you can select any programming language of your choice, Python is the most in-demand. The other programming languages that you can select from are Python, R, SQL, Spark, Hadoop, Java, Tableau, AWS, SAS, Hive, Scala, C++, Excel and Azure.

Data Wrangling: While dealing with massive amounts of data, it is important to understand and know how to deal with its imperfections. To do so you should prepare your data for further analysis, which can be done through Data Wrangling. Good knowledge of this would help you gain deep intelligence within your data by gathering data from multiple channels.

Data Visualization: Data Visualization refers to the graphical representation of the findings from the data. It effectively communicates and leads the exploration to the conclusion. You can use a number of visualization processes such as Histograms, Bar charts, Pie charts, Scatter plots, Line plots, Time series, Relationship maps, Heat maps, Geo Maps, 3-D Plots, and others for effective Data Visualization.

Machine Learning and Deep Learning: A good knowledge of Machine Learning is required when the decision-making process is data-centric. As a subset of the Data Science ecosystem, Machine Learning contributes to the modeling of data and obtaining results. Machine Learning for Data Science includes algorithms such as K-nearest neighbours, Random Forests, Naive Bayes, and Regression Models.

Apart from the technical knowledge, there are some non-technical skills that a person must have to become a successful Data Scientist:

Analytical mindset: As a Data Scientist, your primary job will be the analysis of data. Having an analytical mindset would help you to a great extent.
Creative problem-solving skills: For every individual, problem-solving skill is a crucial skill to have. While it helps in every step of your life it is especially required when you aspire to build a career in Data Science. A person who is creative while solving a problem is greatly valued by employers.
Business thinking: Business thinking is an essential knowledge a Data Scientist should have. This will help you to continuously provide value through the provision of insights that can be acted upon.
As Data Science is mainly about data, you must be curious about the data that you will be dealing with. And you should think practical. It will help you make informed decisions.

How to build a career in Data Science?

One needs to have the knowledge of mathematics, statistics and programming as a data scientist. Since most roles in Data Science bridge IT and management, you can experience both the domains and plan your career moves swiftly.

To build your expertise you can take up online certification courses that are specifically designed for aspiring Data Scientists. The carefully curated course modules of such programs will help you develop these skills and will help you land a job in Data Science. Those who aspire to build a career in Data Science should have all the required expertise and should be open for consistent and continuous learning. There are programs which are specifically designed for freshers and young IT professionals seeking Data Scientist roles.

Data Science is going to be a game-changer not only for the industry but also for your career.