Once named the sexiest job of the ‘21st century’ by Harvard business review, Data Science and Data Science field is one of the most reputed fastest-growing, and profitable careers across the globe. From businesses to non-profit organizations, and to government institutions, an infinite amount of data can be refined, sorted, interpreted, and applied for multiple purposes. In today’s digital world, we gather a tremendous amount of data every day, which requires modern data processing tools and methods, and this is where a Data Scientist come into the picture.
When talking about how to become a Data Scientist, it could be tough to unwrap the various complex analytical problems a Data Scientist solves every day. As there is an infinite amount of data and information available, the demand for Data Scientists has also increased. In fact, people are taking a data science course in Hyderabad, Bangalore, Chennai, and many other places to gain the right skills and start a career in this field. Let’s closely look at how you can step into a booming career in the data space as a Data Scientist.
What is a Data Scientist?
A Data Scientist is an individual who extracts, interprets, and analyzes Big Data to align with the business’s overall goal and purpose.
In simple words, Data Scientists are trained professionals who gather, organize and analyze the data to help organizations and businesses of every industry to achieve their goals.
Data Scientists constantly play with the data from its raw state and often create algorithms that are used to present it in a cleaner and simpler form that teammates and organizations understand. They can represent the data in a visual context or data visualization, observing the clear pattern, which can be helpful for the organization.
Data Science in Real World
Let’s take a real-world example to understand how Data Science works.
Netflix is one of the biggest OTT platforms globally and has around 214 million users to date. The company uses advanced Data Science metrics that allow them to present better show or movie recommendations to its users. Now, you must be wondering how they do it.
Netflix measures user engagement such as;
- What device do you use
- When did you pause, forward, or rewind
- Your browsing pattern
- What kind of content do you watch, mostly
- What time and week do you watch content
Using all these pieces of information, Netflix recommends the content that you would like and watch.
How To Become a Data Scientist?
Data Scientist comes from a wide range of educational backgrounds but mostly technical knowledge, including programming languages, maths, business, and statistics.
To become a Data Scientist, there are fairly seven skills you need to master:
- Programming languages
- Database knowledge
- Statistics and Probability Analysis
- Concept of Machine Learning
- Working knowledge of Big Data Tools
- Data Cleaning
- Online training
- Programming Languages – The first step to starting your career in the Data Science world is to master any programming language such as R or Python. R is a free software for statistical computing and graphics, widely used by data miners and statisticians for developing data analysis and statistical software. Wherein Python is an open-source programming language and one of the most preferred coding languages adapted by Data Scientists. In addition, Python is easy to understand and supports various libraries such as NumPy, SciPy, Matplotlib, etc.
- Database Knowledge – Database knowledge is required to store, extract, and analyze data using SQL. Structured Query Language (SQL) is the domain-specific language to extract and communicate data from the database.
- Statistics and Probability Analysis – Having an in-depth knowledge of statistics and probability is essential to becoming a Data Scientist. Statistics is developing and studying methods of collecting, analyzing, and presenting factual data. Probability is the corrective measure of an event that will occur.
- Concept of Machine Learning – According to Google, Machine Learning is a method of data analysis. It is a part of Artificial Intelligence that provides systems the ability to learn automatically and identify patterns to make decisions without being explicitly programmed. Being a Data Scientist, it is one of the crucial steps wherein one has to build various algorithm models using Machine Learning algorithms to solve any problem.
- Working Knowledge of Big Data Tools – Big Data tools such as Hadoop, Apache Spark, Tableau, and Talend deal with huge and complex data that traditional data processing tools can’t handle.
- Data Cleaning – Being a Data Scientist, most of the time goes into cleaning the data set, removing unwanted values, and handling missing values. It can be achieved by using the Python libraries using Panda and Numpy. Although, you should know the basics of Microsoft Excel, Functions, Formulas, Pivot Table, VLookup, etc.
- Online Training – Taking online Data Science training and boot camps is common among all data enthusiasts. These online training and boot camps help you enhance your skills with live interactive classes, doubt sessions, industry projects, and live training. So, if you are looking forward to a course, then check out Simplilearn’s Data Scientist Certification, in collaboration with IBM, that will provide a hands-on experience to key technologies including Python, R, Machine Learning, Hadoop, and Spark
Data Scientist Salary
No matter what source you look at, the salary of a Data Scientist professional is beautiful to look at. According to PayScale, the average salary of a Data Scientist is $96,961 per year. An entry-level Data Scientist with less than 1 year of experience can expect to earn an average salary of $85,242. Data Scientists with 1-4 years of experience can expect to earn a salary of $95,779 per year. In the mid-level career of a Data Scientist with experience of 5-9 years, the salary goes around $110,261 per year. Finally, a Data Scientist with experience of 10+ year earns an average salary of $121,878 per year.
Although the salary depends upon the location, company, skills, and expertise one brings to the table during the interview.
Conclusion
The world of Data Science is continuously developing, and Data Scientists are trained to stay at the leading edge of information and technology. To become a Data Scientist, you need to learn and master the skills mentioned above, such as programming languages, database knowledge, Big Data, and its tools, machine learning concepts, and data cleaning. In addition, the knowledge and skills you will gain in working on live projects, case studies, and simulations after completing a course or boot camp will set you ahead of the competition.
