Yes, data science is a very good career with tremendous opportunities for advancement in the future. Already, demand is high, salaries are competitive, and the perks are numerous – which is why Data Scientist has been called “the most promising career” by LinkedIn and the “best job in America” by Glassdoor.
India contributed to 9.4 per cent of the total global analytics job openings, a rise from 7.2 per cent in January 2020. In addition, recruitment services firm Michael Page India's 'The Humans of Data Science' report revealed that data science will create roughly 11.5 million job openings by 2026.
The Bureau of Labor Statistics projects 31.4 percent employment growth for data scientists between 2020 and 2030. In that period, an estimated 19,800 jobs should open up. Data scientists use technology to glean insights from large amounts of data they collect.
You can think about the data increase from IoT or from social data at the edge. If we look a little bit more ahead, the US Bureau of Labor Statistics predicts that by 2026—so around six years from now—there will be 11.5 million jobs in data science and analytics.
A data scientist with a fair amount of experience can make up to US$800K in the US, and in India, nearly 90 lakh rupees per annum.
Data scientists are about average in terms of happiness. At CareerExplorer, we conduct an ongoing survey with millions of people and ask them how satisfied they are with their careers. As it turns out, data scientists rate their career happiness 3.3 out of 5 stars which puts them in the top 43% of careers.
The work environment of a data scientist can be quite stressful because of long working hours and a lonely environment. It's strange to note that despite the multiple collaborations required between the data scientist and different departments, most of the time, data scientists work alone.
Reason #1: Mismatch in Employer Expectations
You spend thousands of hours learning statistics and the nuances of different machine learning algorithms. Then, you apply to dozens of different data science job listings, go through extensive interview processes, and finally get hired by a mid-sized organization.
Data Science can be really fun if… Data science is a rare job where you get to do all of the cool stuff together: mathematics, coding, and research. A job where you can read a research paper in the morning, write down the algorithm in afternoon, and code it up in the evening. It is really fun!
There are no sharp upturns or downturns. This could suggest that data science won't just abruptly disappear in the near future. If anything, there would be a slow decline over time, of which there currently isn't really any evidence.
Yes, Data Science is overrated. Data science is a "concept to unify statistics , data analysis , informatics , and their related methods" in order to "understand and analyze actual phenomena" with data.
So is data science still a rising career in 2021? The answer is a resounding YES! Demand across the world for Data Scientists are in no way of slowing down, and the lack of competition for these jobs makes data science a very lucrative option for a career path.
Scientists say they've identified the jobs, hobbies, and traits deemed to be the most boring. Data analysis is considered the most bland job and sleeping is among the most boring "hobbies."
Data scientists usually work standard business hours, between 8 AM and 5 PM, Monday through Friday. Some organizations are allowing more flexibility where core working hours (say, 10 AM to 3 PM) are observed, and beyond that employees are given the freedom to work different schedules.
Like any other field, with proper guidance Data Science can become an easy field to learn about, and one can build a career in the field. However, as it is vast, it is easy for a beginner to get lost and lose sight, making the learning experience difficult and frustrating.
You don't like to work for long periods of time alone
Data science can require extended periods of concentration. This work is best done alone and with minimal interruption. If you are a highly social person and desire constant interaction, a data science career might be too isolating.
Several reasons explain why a career in data science, spent working on machine learning algorithms and the like, is losing its charm. Here they are: Inability to kickstart careers: Fresh-out-of-university candidates want to start off in data science, but most jobs require 2–3 years of experience.
If you want a high-paying, dynamic job in an in-demand and rapidly growing field, data science may be worth looking into. According to the U.S. Bureau of Labor Statistics, the job outlook for data scientists is projected to grow 22% from 2020 to 2030, much faster than the average for all occupations.
Data Science is required by businesses of all sizes to make decisions, analyze market trends, reduce losses, and increase profits. The role of a Data Scientist has become the most sought-after profession due to the increase in data and its connected industries.
Here are a few reasons that make data science so exciting. Being a data scientists is essentially having a job as a detective, the modern day Sherlock Holmes. The industry is great for those with curious minds who love solving everyday puzzles. Working with data allows you to play with knowledge.
Altogether, the amount of learning that is required to become a data scientist cannot be done in a mere time period of six months.
Construction workers are the #1 happiest job for a reason—they do what humans are built for! They plan, move and use their bodies, and get to see their creative works come to life. Not all construction jobs are easy to jump into, however.
A data scientist's daily tasks revolve around data, which is no surprise given the job title. Data scientists spend much of their time gathering data, looking at data, shaping data, but in many different ways and for many different reasons. Data-related tasks that a data scientist might tackle include: Pulling data.
Those who go the university route can become a data scientist in 3–4 years. For the 75% who decide to get their master's in data science, it may take an additional 1–2 years. The total time can be bumped up to 5–6 years. While self-studying has the potential to be the shortest path, this depends greatly on the student.