By Kalibrr Guest Post on September 27, 2019
The world now revolves around millions of data. But if you think about it, is data worth anything without the expertise of Data Scientists?
The rapid upsurge of Big Data has made it mandatory for organizations and enterprises to gather relevant industry data. This, in turn, pushes them to invest in the right talent who can transform that data into something meaningful. And that's where Data Scientists come in.
Who is a Data Scientist?
To put it simply, a Data Scientist is an analytical data expert who combines all qualities of a scientist, an analyst, a mathematician, a statistician, and an explorer-cum-trend spotter. By using their technical knowledge and skills in these multiple domains, Data Scientists exploit, analyze, and interpret data to find solutions to diverse and complex problems. They are professionals who have the expertise to implement pioneering Big Data and Machine Learning technologies and tools to gain valuable insights hidden within large datasets. And the cherry on top is that Data Scientists combine the best of both worlds - Business and IT. These are the reasons why they are one of the most highly sought after and well-paid professionals in the industry today.
Organizations and companies "need" Data Scientists to dig deep into data and uncover meaningful insights that can contribute to data-driven decision-making. As more and more companies realize the potential of Big Data, they are creating the demand for Data Scientists, thereby further driving up their professional value. Not for nothing did HBR declare the job of a Data Scientist as "The Sexiest Job of the 21st Century!"
Tech giants like IBM, Microsoft, Oracle, Google, Apple, Deloitte, MuSigma, Accenture, Amazon, and Facebook are some of the top recruiters of Data Scientists. According to a 2018 LinkedIn report, while the US is the largest market for Data Scientists, there is also considerable demand for Data Scientists in the UK, France, Germany, and India.
So, are you interested in taking advantage of this golden opportunity and contribute to the Data Science community? If so, here's a simple guide to becoming a Data Scientist!
How to Become a Data Scientist?
The job profile of a Data Scientist is highly diverse and versatile. Hence, you must acquire many different skills in different domains to become a successful Data Scientist.
1. Prepare yourself for Data Science.
It's never too soon to start preparing yourself for a career in Data Science. Even before you start your graduate/postgraduate studies, you can begin acquiring the foundational skills by pursuing Data Science Courses. For instance, you can master one or more programming languages most commonly used in Data Science such as R, Python, and Java. You can also brush up on Applied Mathematics and Statistics - both are an integral part of Data Science. An early headstart will not only help you to ease into Data Science, but it will also help you determine if Data Science is the right career fit for you.
2. Obtain a Graduate Degree.
Generally, a degree in Computer Science, Mathematics, Statistics, Information Technology, or Data Science are best-suited specializations for a career in Data Science. No matter which specialization you choose to complete your graduate-level studies in, you should also simultaneously hone your knowledge and skills in coding, database architectures, data munging, data ingestion, data visualization, SQL/MySQL, and ML and AI. You could also look for graduate-level internships in Data Science or related fields for real-world job experiences.
3. Get a job.
Although this step can follow after the completion of your postgraduate degree, you may choose to get an entry-level job before you go for postgraduate studies. Many companies hire graduate-level fresh graduates to fill up entry-level Data Science jobs like Junior Data Analyst, or Junior Data Scientist, or Associate Data Scientist, to name a few. Also, having a few years of work experience is often preferred by reputed companies.
4. Complete your Postgraduate Studies.
Advanced degrees are highly valued in the field of Data Science. The higher your educational degree, the higher the compensation you can get. The majors for postgraduate studies are similar to that of graduate-level studies (Computer Science/Mathematics/Statistics/Information Technology/Data Science). However, certain companies also accept STEM degrees like Engineering, Biotechnology, etc. After completing your postgraduate studies, you can also opt for a Ph.D. in a chosen discipline.
5. Don't stop learning.
Data Science is an emerging field. New advancements are being made every day. Hence, you must always try to stay updated with the latest trends and happenings in the Data Science community. Read books, articles, journals, newsletters, and blogs on Data Science and related fields to boost your knowledge.
Apart from obtaining degrees and getting a job, here are some skills you must acquire to become a Data Scientist:
Mathematics (Matrices and Linear Algebra Functions, Hash Functions and Binary Tree, Relational Algebra, Database Basics, Extract Transform Load, and Reporting vs. Business Intelligence vs. Analytics)
Statistics (Descriptive Statistics, Exploratory Data Analysis, Percentiles and Outliers, Probability Theory, Bayes’ Theorem, Random Variables, Cumulative Distribution function (CDF), Skewness, etc.)
Machine Learning and Artificial Intelligence (Supervised Learning, Unsupervised Learning, Reinforcement Learning including Linear Regression, Logistic Regression, Decision Tree, Random Forest, K Nearest Neighbor, k-means clustering, etc.).
You can also consider taking up professional certifications in Data Science such as Data Science for Python, Data Science with R Programming, SAS Certified Advanced Analytics Professional, and Microsoft Certified: Azure Data Scientist Associate, to name a few.
To conclude, companies of every size and across various sectors of the industry are using data to enhance business operations, increase revenue, and boost customer satisfaction. So, everyone in the game is always on the hunt for talented Data Science professionals who can efficiently handle and manage Big Data. Looking at the pace at which jobs in Data Science and Big Data are growing, it is safe to say that the future for Data Scientists is extremely promising.
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