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Why Data Science Will Be The Most Lucrative Career of this Decade

Why Data Science Will Be The Most Lucrative Career of this Decade

Data science concentrates on analyzing data for various purposes. It entails examining, cleaning, converting, and modeling data in order to gain important insights. With these insights, data scientists can find the answers to questions such as what occurred, why it occurred, what will occur, and what can be accomplished with the results.

Big data is the top trending tech field right now. In the past few years, the requirement for Data Science jobs posted has steadily increased. Data science experts must distinguish themselves to land a job. 

What you should know about big data and data science

According to a report by HBR, Indeed jobs advertised for data scientists had increased by 256% in 2019, and the US Department of Labor anticipates that data science will rise more rapidly than almost any profession from now to 2029. It helps that the sought-after job pays well: The average salary for a skilled data analyst in California is close to $200,000.

Meta is among the companies that have had a huge impact on the world of technology and information interactions. Our product-related discussions and thoughts transform into online ads because social media apps such as Instagram and Facebook track both our online and offline activities. If you’ve seen a Facebook video that shows a “flashback” of comments, likes, or images, similar to the ones you would see on your birthday or a special occasion, is one of the many instances of how Facebook makes use of Big Data.

COVID-19 also accelerated the growth of Data Science. As the pandemic hindered supply chain operations and brought economies worldwide to a pause, businesses started requiring more precise and timely information. Because of this, companies’ requirements for data analytics are going through the roof.

How great is the demand for Data Scientists? 

Every day, companies generate an insane amount of data, which is necessary to optimize revenue and make both major and minor decisions. This has resulted in high demand for data scientists in both new businesses and established businesses.

According to the International Data Corporation (IDC), “The global data sphere will grow from 33 zettabytes in 2018 to 175 by 2025. Nearly 30% of the world’s data will need real-time processing.”

Companies are also increasing their investment in data science to prepare for increased competition in their industries. Here is a sneak peek at some of the entry-level job opportunities for Data Science graduates:

Job TitleDescriptionAverage Salary
Remote Junior Data Scientist at a Heath startupThe organization is looking for Knowledge of statistics/probability and machine learning. Employee must be comfortable in Python, including libraries such as scikit-learn.$50,000-$60,000
Junior Data Scientist at an international financial institutionThe role calls for coordination and communication to stakeholders for a Cloud-first environment, the ability to create strong data pipeline projects and suitable AI models, expertise with database systems and information warehouses, and demonstrated expertise in top data science practices such as collecting data, investigation, and pipeline strategic planning.$70,000-$1,00,000
Jr. Data Scientist at an IT recruitment agencyResponsibilities include maintaining quality of the data at all stages of collection and processing, including data source information and ground truth generation. Employee will create, test, and release truly innovative models that enhance the overall customer experience and track their impact over time.$65,000-$80,000

5 Steps to Getting Your First Job in Data Science

There are numerous data-related roles available globally, and there is an ever-increasing demand for highly skilled individuals—HBR says that data science is the hottest job right now, with every remarkable advancement in artificial intelligence covered in the media.

If you want to be a part of the data science boom, here’s how to get started in the data industry.

1. Ascertain which career you enjoy the most

A data team typically consists of several people, including a data analyst, a data scientist, a machine learning engineer, and a data engineer. The primary goal of any analytics team is to develop data-driven business solutions. This is a broad and perhaps overstated goal given that there are numerous ways to accomplish it, including:

  • Developing dashboards that enable upper leadership to make sound strategic decisions
  • Creating models that can forecast different variables such as retail prices or customer propensity
  • Minimizing time consumption for the necessary information that may assist the customer in deciding on our product
  • Identifying patterns that could indicate market trends or public needs

2. Learn the required programming languages

The first step is to learn how to code. Though some say it’s no longer necessary to understand programming to deal with data, most data scientists and engineers are still using programming languages in their work. Python is the main language you need to know: Aside from data manipulation, it can also be used to build the codebase of a webpage, a mobile application, and numerous other projects.

3. Dive deep into your preferred area

A 30-hour online course will not turn you into a data scientist, a data engineer, or even a data analyst, but this is an excellent place to start if you’ve never worked with data before. Start by checking out these data science courses from Udacity and Section4.

4. Keep learning and upskilling

If you work with data, you need to be aware of the other functions in the data ecosystem. Data engineers must comprehend the requirements of scientists, be able to create data visualizations, and know which features must be created manually each time they are required given that they are not accessible on the data lake. You need to stay abreast on the latest trends in the industry, and you should be able to keep up with the latest innovations and updates in your tech stack.

5. Make an eye-catching portfolio

Data scientists have plenty of competition in their space, and standing out is a must to get hired. Working with data is difficult and requires continuous learning and upskilling. By taking on projects and solving problems, you’ll demonstrate that you can perform well in your role.

Find the data science course that works for you

Once you get your foot in the data science industry, you’ll be unstoppable. Data science offers several opportunities for career growth, and you’ll have the flexibility to move about and accept jobs that interest you. The best part is that, according to studies, the data science industry will more than double in the coming five years—so learning data science is the best decision you can make this year.

There is a flood of inauthentic, cliched, and underwhelming data science courses available on the internet. Avoid these unproductive courses by using SkillUpgrade to find interactive online data science classes that are ideal for you. The courses we recommend will support you in launching your data research career by finding the best online subjects and research courses that correspond to your goals.



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