Data science as a career option is fast gaining prominence. According to a Forbes report, Data Scientist has been named the best job in America for three consecutive years, with a median base salary of $110,000 and over 4,524 job openings. Let’s see how to become a Data Scientist and follow up a career with tremendous job opportunities.
According to Glassdoor’s 50 Best Jobs In America For 2018 research, Data Science Profeessional jobs are ranked among the 50 best jobs based on each job’s overall Glassdoor Job Score.
In this discussion on how to become a data science professional, I will bring to light certain aspects that go into the making of a data science professional.
I shall also discuss at length how to become a data scientist in India and how long does it take to become a data scientist. I intend to discuss the following in my discussion on how to become a data scientist:
(i) What is Data Science?
(ii) Who is a Data Scientist?
(iii) Essential qualities of a Data Scientist
(iv) Data Scientist Career in India and abroad
What is Data Science?
Data Science may be defined as a multidisciplinary blend of data inference, algorithm development, and technology to solve complex data issues.
Data lies at the core of Data Science. It deals with troves of raw data, streaming in from multiple sources and is stored in enterprise data warehouses.
Data Science is much more than exploring different data layers for meaning.
Data science involves uncovering findings from the collated data and mining the data at a granular level to unravel complex data behaviors, trends, and inferences.
It also includes bringing out latent data insights that are useful in making informed business decisions.
I can cite three classic instances of data science implementation in real-life by industry giants.
1. Netflix
Netflix (world’s leading internet entertainment service with 130 million memberships in over 190 countries enjoying TV series, documentaries and feature films)data mines movie viewing patterns of its subscribers to take note of what drives user interest, their preferences, and makes uses the findings to come up with better business strategies for Netflix to roll out newer packages for sales.
2. Target
Target (the eighth-largest retailer in the United States) identifies the major customer segments within and also identifies the unique shopping behaviors within those segments. This helps to Target to customize its messaging to different user groups.
3. Procter & Gamble
Procter & Gamble (an American multinational consumer goods corporation) makes use of time series models to predict future demand, which helps in better planning for production levels.
How to Become a Data Scientist: Who is a Data Scientist?
The term “data scientist” was coined in 2008 when companies realized the need for data science professionals, adept in organizing and analyzing massive amounts of data.
In a 2009 McKinsey & Company article, Hal Varian, Google’s chief economist, and UC Berkeley professor of information sciences, business, and economics emphasized the need to adapt to technology’s influence and reconfiguration of different industries.
Data Science professionals can identify relevant questions, collect data from a multitude of different data sources, organize the information, translate results into solutions, and communicate their findings in a way that positively affects business decisions.
These skills are mandatory in almost all industries, thereby creating a growing need for skilled data scientists.
How to Become a Data Scientist: Essential qualities of a Data Scientist
As a tech blogger, I have often come across young techies asking the question “How to Become a Data Scientist?”
Quite often, I have discovered that most people live with the wrong perception that a data science professional must always be a mathematics genius or a PhD.
True that research shows that nearly 88% of data scientists have a Master’s Degree and about 46% have PhDs. But the truth is, you may not have either, and you can still be a data scientist.
How to Become a Data Scientist – Technical Expertise
Coding
To be a data scientist you must have an in-depth knowledge of SAS and/or R. Of these, R is generally preferred. Another essential requirement is a strong knowledge of Python coding. Python is the most common coding language that is used in data science along with Java, Perl, and C/C++.
Data science professionals should be able to prototype quick solutions and integrate with complex data systems. Core languages associated with data science include SQL, but let me tell, knowing programming languages is not enough, as a data scientist, you must be able to find creative solutions to technical challenges in order to make your codes work.
This is absolutely essential because data scientists operate within a lot of algorithmic complexity. They must possess a strong mental comprehension of high-dimensional data and tricky data control flows.
Although not a mandate, knowledge of the Hadoop platform is still preferred for the field. Having a bit of experience in Hive or Pig is also useful if you want to become a data scientist.
Statistics
As a data scientist, you must have a thorough understanding of statistics. This means a strong background in statistical tests, distributions, maximum likelihood estimators, etc. almost all companies look for a data scientist with a good knowledge of Statistics.
But for data-driven companies, it is a mandate, where the business stakeholders depend largely on data scientists for making business decisions and strategies for growth.
How to Become a Data Scientist: Data Intuition
A data scientist is much more than a data-driven problem-solver. In addition to your expertise as a master coder, analyst, or statistician, a data scientist should be able to judge data, i.e., understand the relevance of a data chunk, even before mining it.
As a data science professional, you will be required to test a data-driven product that the company wants to develop.
Your data intuition should tell you why it is important, what techniques to be used for processing, and the importance of business estimations.
You must also know what questions you should ask while interacting with data science engineers and product managers. What methods should you use? When do approximations make sense?
Business Acumen
Having strong business acumen is just as important as having a caliber for tech and algorithms. You must be able to clearly align data science projects and business goals.
Knowledge of programming language, coding, machine learning, data visualization, all is important. But as we all know, at the end of the day, business matters, and that comes only from leveraging all of the above to build valuable capabilities and have strong business influence.
Want to more about how to become a data scientist? Watch the following video, which guides you, with a step-by-step approach to becoming Data Scientist:
https://www.youtube.com/watch?v=jMvhFNGGT_0&feature=youtu.be
The video will answer all your questions on how to become a data scientist.
How to Become a Data Scientist in India?
Very recently a read a report on Gartner’s earlier prediction of Indian business intelligence and analytics software market reaching $245 million in 2017, a whopping 24.4% increase over 2016 revenue of US$206 million.
A more detailed analysis of The Hindu Business Line forecasts the addition of around 1.80 lakh to 2 lakh new job creation in 2018.
A ready answer to the question: “How to become a data scientist in India?” would be through a well-defined career plan and a willingness to grow.
Most data science professionals in India start as a data science engineer or data analyst, and with a few years of experience (this may range from 5-8 years), they can try for data scientist roles.
How to Become a Data Scientist with an Engineering or Maths background?
You may be a B. Tech or M. Tech, a Mathematics graduate, or simply a programmer, aspiring to be a data scientist. You may ask yourself the question How to become a data scientist in India? The answer lies in your own hands. Stay updated on data science company requirements.
Make a regular habit of going through by visiting LinkedIn profiles of top data science companies in India, and finding out their areas of service.
Once you are through with their service lines, look up for video tutorials, interviews, and other examples of real-life examples of how data science problems are solved.
Top Data Science companies in India are looking for fresh qualified data analytics resources. Many of the global players in data analytics have set up development centers in India. Keep yourself posted on their job postings and add influencers to your network.
Data Scientist Salary
On average, a data science professional, according to Indeed.com earns, close to $123,000 a year. According to Glassdoor, the average salary for a Data Scientist is $113,436 per year.
According to 2019 Glassdoor survey, the national average salary for a Data Scientist is ₹9, 50,000 in India. A senior Data Science professional may draw a salary of around ₹157,000.
Related job profiles like Data Analyst or Quantitative Analyst may draw a median salary of around ₹21,000 or ₹57,000, respectively.
According to Glassdoor 2019 study, the national average salary for a Data Scientist is $1, 17,345 in the United States. In the UK, the average pay for a Data Scientist is £35,201 per year, according to PayScale.
A Data Scientist’s salary in the UK may start with £25000 and go up to £61,000.
How long does it take to become a Data Scientist?
Well, to answer the common question of “How long does it take to become a Data Scientist?”, I would say, it depends upon you, and the market demand.
If you are already in your final year or final semester, you can start applying for data science professional roles or you also start your career as a data engineer.
You are most likely to land up a job in less than six months. Most companies advertise for interns. Watch out for openings in job portals and business networking sites.
Does a career in data science interest you? Do not be taken away the Data Scientist Salary figures. You must create a killer data scientist’s resume before you apply anywhere. The same applies to Data Analyst.
Wrapping Up
You might be a programmer, a mathematics graduate, or simply a bachelor of Computer Science. Taking up a good Data Science or Data Analytics course teaches you the key Data Science skills and prepares you for the Data Scientist, Data Scientist role (that you aspire for) in the near future. Do not forget to include all your skills in your data scientist’s resume & take a Data Science Internship to get practical exposure.
You may also enroll in a Data Science Course for more lucrative career options in Data Science. Industry-relevant curriculums, pragmatic market-ready approach, exposure to hands-on Capstone Project are some of the best reasons aspiring data scientists and data analysts choose Digital Vidya.
