Why Data Science Jobs are Experiencing a High Demand | Optymize
In this 21st century, data has become an essential component in every other industry as it provides deep insights into performance, growth, and other parameters. Previously the data was only used for estimating profits and loss, nowadays the data is powering the IT and other technological innovation firms to help build an effective solution that can utilize this data to predict future outcomes. For this reason, data science jobs are becoming the new norm in the tech industry that are expected to power tech giants with more accurate data. Emerging technologies such as AI and Machine learning play a key role in giving the data huge popularity and demand as it requires data to make models that can predict future activities giving rise to a new technical niche known as data science. Experts say data science is staying forever as it will control every other firm’s future and will decide what will happen in the coming years. For this reason, every company is feeling the necessity to gain a strong grip on data science technology. Having analyzed the demand, companies are eager to hire data science experts worldwide, giving a huge boost to data science jobs. In this post, we will clear some key facts on why these jobs are in high demand. What is Data Science Data science is the study of data which involves developing, storing and analyzing the data to effectively extract useful information. The prime goal of data science is to gain insights from both organized and unorganized data to make possible analytics and help provide effective solutions. Why Do We Need Data Science We need data science for various reasons and for various niches to improve their performance by analyzing previous data. For example, an organization’s yearly profit and loss sheet, where the organization always keeps on improving using the data to get maximum benefits. Consider an example of a weather forecast- have you ever wondered how they determine and put these numbers so we can understand the weather conditions. Well, weather conditions are measured by scientific equipment and satellites, and the data collected by both are put together and further analyzed by a team of scientists. If the weather conditions appear to be harsh then the warning is issued. This is how data helps determine weather conditions. In this digital age, a huge amount of data is produced every day as everyone seeks to put their presence on the internet. According to research data we produce more than 90 zettabytes of data every day by using different internet and software resources such as social media and others. Imagine if we could use this data to make analytics that can be further used to make our lives easier, sounds exciting right, it is. Data science can greatly help us bring this solution to the real world and with thriving innovations like IoT, AI and Machine Learning we can make AI-Based solutions such as human behavioral adaptation by robots, and other autonomous software that can predict the market situation in the future. Is Data Science A Good Career Considering its demand, the data science industry is expected to boom in millions, according to the US Bureau of Labor statistics there will be 11.5 million jobs worldwide by the end of 2026, the data also suggest the jobs market will keep on nourishing creating more opportunities for freshers. Hence, there is no doubt that it’s a good career. Data science is a vast area of study hence it’s filled with various opportunities, it offers various job roles so freshers can opt for this immensely growing niche to nourish their career, below are some of the best data science jobs that you can opt for- 1. Data Scientist. 2. Data Administrator. 3. Data Engineer. 4. Data Architect. 5. Data Analyst. 6. Machine Learning Engineer. Is Data Science High Paying Undoubtedly yes, as it’s an emerging technology and considering the lack of supply to power its relevant industries, data science jobs come with handsome pay which can make developers switch from their previous roles and opt for the above-mentioned job roles. Hence, the salaries offered in this job market are impressive. In USA- In the USA, the average median salary of a data scientist is $140,742 per year. In UK- In the UK, the average median salary of a data scientist is $65,7628 per year. In India- In India, the average median salary of a data scientist ranges between $9000-$15000per year. Why Data Science Jobs Are In Demand There are various reasons why these data science jobs are in demand, and many might surprise you as they don’t belong to the tech industry or any related firm. Whatever the reasons might be, we can’t ignore its demand. let’s see some parameters that caused a huge job growth- 1. Supply And Demand When the internet started emerging in the 90s, various software companies like Apple, Microsoft and IBM started hiring programmers and web developers in huge amounts. The reason for this was to make available their software solutions in every other company so they can achieve maximum benefits. As computer science brought software solutions that made businesses operate with ease, the demand for these software and web solutions surged. Software companies in the 90s realized this fact and thought of hiring a huge no. of programmers, but the internet was a relatively new concept at that time and no one knew what software is and what a programmer does hence, there was an increasing demand for programmers while the supply was low. This caused IT firms to gain more and more popularity as they were offering their programmers huge salaries and everyone thought of it as the best career they could ever imagine. There is a similar situation with data science as nowadays it’s a relatively new concept and this firm still lacks experienced data scientists, data administrators and other roles which can help boost industries to a greater extent. Hence, the demand for data science jobs is high whereas the supply is low causing immense popularity and demand. 2. Huge Data Production As the data is being produced at a huge amount there will be a huge requirement of data professionals to manage and analyze this data. According to research data, 163 zettabytes of data will be produced by the end of 2025, as compared to 90 zettabytes in 2022. This humongous data will require management and analysis to use for future reference and most data science jobs focus on the same goal. Hence, this industry is a perfect match for managing and analyzing this huge data to build effective solutions. AI and Machine learning are one of their huge consumers as they focus on building models that can use previous and present data to predict the future activities of any object. For example, comets, by using technologies such as machine learning, ML engineers can use the previous data of the comets such as their velocity, speed, orientation and other parameters and build a model that can predict its upcoming activities so scientists can be aware of its trajectory. 3. Data Science In Educational Institutions Considering the rising demand for data science, educational institutions around the world have accepted this niche as their new computer science sub-branch which falls into the database category. They have now started building the curriculum for this branch to make college students have a strong grip on this niche for future job opportunities. This is a huge step for the data science niche as it’s now entered as a major in universities, giving a huge boost to its popularity as it will be considered one of the best computer science branches by college students. This will also help the data industry as more employees will give it a huge momentum and the industry will flourish in the tech. Not to forget as it’s a relatively new technology it will experience technological enhancements and innovations like other computer science majors, which might give birth to whole new different niches. 4. Industry Demand Data always played a crucial role in building a strategy which can elevate a business from zero to Multinational corporations, up until now only insurance, finance companies and banks used to play with the data for the greater business but as industries are started realizing data science and its benefits they have taken necessary step to make sure they use this technology to enhance their industry and become a giant among their competitors. For this reason, various industries have started hiring data scientists and other data science jobs to build solutions that can utilize data and build efficient software solutions. For example- companies can build various models with the help of data scientists and ML engineers to help predict their profit and loss, growth of business, frauds and many other parameters. This can help companies to improve their operations and reduce loss, bringing more clarity to their growth through accurate analytics. Remote Data Science Jobs And Their Benefits This parameter plays a huge role in boosting the demand for jobs, as remote candidates have tons of experience in working with data science and data analytics. Remote and freelance candidates are often hired for the crucial roles because those roles require a deep understanding of relevant technology and heavy brainstorming to solve the issue that occurred in the system. Because of their expertise, they solve these issues flawlessly by addressing this issue and removing it with an optimum solution. freelance candidates’ skills outmatch the in-house team because they have served many big industries that faced these crucial errors. Benefits of Remote Jobs Faster Product Development- As companies opt for freelance data science jobs they will heavily focus on product development, as remote team skills outmatch the in-house team talent they can bring an effective solution at a much faster rate. Considering the expertise they have companies can hire multiple remote teams that can boost their product development in no time and can have 24*7 product development. Cost-Effective Approach- Remote data scientists operate from different countries around the world having huge currency and cost of living differences, this means their economical conditions may not be as strong as compared to employers’ countries, so they can hire them at reasonable pay and in return get the top-notch software models. And not to forget they will be saving money on office costs such as its maintenance, water bills and electricity bills, hiring and training costs of in-house candidates etc. Increased Market Reach- Freelance data roles can increase the market reach of employers’ business in their region by acting as brand ambassadors, and can further engage in developer and data science communities where they can share their experiences and can attract more clients for their company expanding market reach in different areas. Conclusion Data science is a relatively new niche and as we know a new niche is always in demand till it gets more audience, with the increased data production and other factors such as industry demand, data science jobs are in high demand. On the other hand, AI, Machine learning, and IoT utilize and heavily depend on data to build software solutions and models that can help humanity achieve greater goods. Hence, these technologies also play a major role in nourishing the data industry. There is no doubt this demand will create a chain of opportunities that will power this industry to nourish further with new innovations giving birth to new niches. This rise in data science will bring more planned and proper execution of strategies which will further enhance every other organization to improve their business objectives.