This article is the continuation of of the Major reasons for becoming a data scientist - part 1
3. Base Wages That Are Difficult to Beat (Plus Benefits!)
Being in such a new and in-demand industry as data science, where there are so few competent individuals, will inevitably result in a competitive compensation base and growth window. Data science is not an exception. As of April 2021, the average base pay for a data scientist was $114,673, according to Glassdoor. This is one of the highest average base salaries in any industry and higher than the average base salaries for jobs in professions like software engineer ($103,349), computer scientist ($102,690), and data analyst ($66,842).
We encourage you to continue your current research into the career outlook in the city you currently reside in or where you intend to further your career. Remember that these statistics are constantly changing and can vary greatly depending on where you live and the type of company you work for. Master the statistics and other data science tools with the best data science course, co-developed by IBM.
Naturally, you can anticipate the salaries to climb once you devote the effort to properly establish yourself as a mid-level data scientist or even take on a managing job.
This may exceed $200,000 for a reputable business. Not only that, but many firms will also provide sizable annual bonuses and even shares or stocks as extra benefits, especially for a position as necessary as a data scientist and the link between the work produced and the success and general profitability of the business.
Speaking of benefits, data science is one of the best jobs that typically permit you to work entirely remotely. Working from home is a perk that has always been advantageous. Other professions with similarly high average base salaries, such as medicine, law, and engineering, frequently lack access to this benefit.
Making a lot of money may appear mercenary when mentioned as a primary motivation for pursuing a particular career. It should go without saying that no amount of money can make a job worthwhile if you do not genuinely enjoy it. Although it makes sense that employment security and benefits play a significant role in how, when, and where a selected career path is launched, if not act as the deciding factor entirely. Data triumphs in that field of consideration and management. (Almost paradoxically, there is data to support this.) If you are passionate about data science and possess the necessary abilities and knowledge, you are well-positioned for a highly lucrative career that offers a comfortable, steady income and permits you to work from home to provide a solid foundation for your family and your life.
Glassdoor's claims that data science is one of the top-paying occupations and one of the best for work-life balance serve as additional proof of this comfort and stability. That combo is quite challenging to defeat. With Learnbay’s data science course online, one can accomplish a lucrative career in top MNCs.
4. A Field in Constant Change
The Economist claims that data has replaced oil as the most valuable resource on earth. This is the top motivation for pursuing a data science job or education. In comparison to what we discussed above about data science's graduate influx into the public school curriculum as a stable subject and the relative unfamiliarity of this fact to future or emerging students and professionals, the reason it is at number four on this list is because
career sector choice.
The presence of data science in conventional education still needs to correspond to predictions of its importance to or contribution to our society, including the number of jobs available to graduates.
According to estimates, 97% of all businesses typically use it when making strategic decisions. The subject of data science is developing daily due to the extraordinary volume of new, valuable insights that businesses are receiving via the use of data about their current and potential customers.
One aspect that makes data science such an appealing career path is its constant evolution. You'll learn a wide range of new skills that will allow you to use data to help businesses achieve their goals and to investigate the fascinating new industries that data science is spawning, such as artificial intelligence, machine learning, big data, and others.
Artificial intelligence (AI) is presumably already recognizable to you, at least conceptually. AI employs a variety of algorithms to carry out autonomous tasks and comprehend correlations between various kinds and types of data to mimic human intelligence in computers. A branch of artificial intelligence called machine learning focuses on creating computers that automatically and without explicit programming learn from the past.
Machine learning and artificial intelligence (AI) are methods that help data scientists analyze data more precisely and quickly. The available data is becoming more and more complex, making it difficult for us to understand it on our own as data science develops. Machine learning, which is utilized in products we use every day, like Spotify's song-selection algorithms and Google's search engine, enables machines to perform much of that labor-intensive work for us. Although still in its infancy, machine learning is beginning to play a part in innovations as varied and significant as self-driving cars and cancer diagnosis. Machine learning may seem like a vague idea to some, yet it's a science that affects people on a very personal level, a realistic, commonplace, and human level.
The potential that data science brings will expand along with it. It would have been challenging to predict where the fields of data science, AI, and machine learning would lead us ten years ago. Although it is nearly certain that we will be on a path of growth and expansion, it is equally difficult to forecast where we will be in ten years. If you decide to pursue a career as a data scientist, part of the answers to those questions will depend on you and how you have influenced the industry over your job.
5. Many Options for Career Development
We've shown why a career as a data scientist is highly gratifying, but ultimately you may feel the need to move on to a different position. You'll be well-positioned to excel in one of the broadest ranges of subsequent jobs in any industry with a foundation in data science.
Suppose you choose to continue only in the data science field. In that case, you may always rise to senior or lead data scientist positions in management, which can pay you tens of thousands of dollars more while giving you more authority and the chance to direct your organization's work. You might also decide to specialize in a field like data engineering or machine learning engineering and take a targeted approach to job advancement.
However, there are other ways to go. Data science is not simply an IT position, as we've mentioned; it's also a business role. Working with C-suite executives, data scientists frequently interact with the VIPs at their organization. Along the way, they're addressing business issues and expanding their network of contacts while collaborating with the company's real leaders. As a result, many data scientists go on to work in executive positions like chief data officer.
However, these positions may only need a little data work daily, so you should pursue data degree programs that align with your anticipated future aspirations within the sector. Many top universities today that grant degrees in data science have built their academic programs and curricula around an understanding of this commercial dynamic, leading to degrees in business or vice versa.
You can also go it alone and launch your own company or brand as a data science consultant by leveraging your business expertise, communication abilities, and network of contacts. This will give you the freedom to select your own customers, industry emphasis, methods, and working hours. In more detail, returning to our number one reason for becoming a data scientist, you'll be able to adapt and modify your data-driven effect on your community or global trends by contributing your unique ideas to the ever-evolving technique and value of data.
In the end, the decision is yours since, after working in the data science sector for five to six years and having results to show for it, you can choose your own path in your preferred domain. If you’re a working professional starting from scratch or want to upgrade your skills, do check out the online data science course. Gain the experiential learning from industry experts and land your dream job with 97% hike.
There are no comments for this story
Be the first to respond and start the conversation.