According to Glassdoor, the best job in the United States has been “data scientist” for the past four years. The demand for data scientists is accelerating, and the U.S. Bureau of Labor Statistics says there will be a 27.9% increase in data science jobs from 2016 to 2026. Even though there is a significant need, it is clear that there are not enough skilled masters in data science.
“Everyone says there aren’t enough people who can do data science,” Daniel Gutierrez, Managing Editor, insideBIGDATA, told Forbes. A master’s degree in data science or data analytics is a good choice if you like using computers, doing maths, and finding solutions by looking at a lot of data.
What is Data Science?
Martin Schedlbauer, a PhD and data science professor at Northeastern University, says, “data science is used by computing professionals who have the skills to collect, shape, store, manage and analyse data as an important resource for organisations to make data-driven decisions.”
Almost everything you do with technology involves data, like the things you buy on Amazon, what you see on Facebook, Netflix recommendations, and even your face, which is used to unlock your phone, and this is what you exactly learn by enrolling in the masters course.
Amazon is an excellent example of how helpful it can be for shoppers to collect data. It keeps track of what you’ve bought, how much you paid, and what you’ve searched for. This lets them customise your homepage to fit your needs better. For example, if you search for camping gear, baby items or groceries, Amazon won’t send you ads or suggestions for geriatric vitamins. Instead, you’ll see things that might be useful to you, like a small camping high chair for babies.
Why is Data Science Important?
While data science master courses help companies sway consumer behaviour, the value of data collection goes far beyond the retail sector.
By using data science to create wearable trackers, encouraging people to adopt healthier habits, and warning them of potentially significant health conditions, we can better the general public’s health.
Data can also be used to enhance diagnostic precision, speed the development of targeted therapies, and halt the spread of infectious diseases. Following West Africa’s Ebola outbreak in 2014, scientists could monitor the virus’s progress and pinpoint where it was most likely to cause fatalities. Using this information, health officials could stop the outbreak before it spreads globally.
The field of data science is increasingly important in a wide variety of areas. Farmers utilise data for efficient food production and distribution, food suppliers use it to reduce food waste, and nonprofits employ it to increase fundraising and anticipate funding needs, for example.
Data science is an attractive field of study not only because it is cutting-edge and lucrative but also because it has the potential to serve as the economy’s fulcrum.
In-Demand Masters in Data Science Careers
Experts in data science are in massive demand across a wide range of industries. Half of one per cent of the American workforce is not even employed by the five largest tech giants (Google, Amazon, Apple, Microsoft, and Facebook). However, entry into these high-paying, high-demand fields typically necessitates some college or university experience.
While there are exceptions, a solid educational background is typically required to obtain the depth of knowledge required to be a data scientist, as reported by KDnuggets, a significant site on Big Data. 88% of data scientists have at least a master’s degree, and 46% have PhDs.
Here are a few of the most in-demand fields in which an advanced master’s degree in data science may get you started.
● Data Scientist
Average Salary: $117,212
Finding, cleaning, and organising data for businesses are typical job duties. To uncover patterns that can help an organisation and drive strategic business decisions, data scientists need to be able to analyse vast amounts of complex raw and processed data.
Average Salary: $131,001
Machine learning engineers must build data pipelines and provide software solutions to clients. They often require expertise in software engineering, as well as programming and statistical skills. Furthermore, they not plan and execute the development of machine learning systems but also test and experiment with them to ensure they are functioning as intended.
Average Salary: $137,053
This job typically involves investigating and documenting novel data approaches and algorithms for application in adaptive systems, such as supervised, unsupervised and deep learning methods.
Average Salary: $129,000
Everyday duties include monitoring the actions and interactions of business applications and their users. Application architects are concerned with more than just the overall design of an application. The applicants holding Masters in data science can also design the architecture of its individual parts, such as the user interface and the underlying infrastructure.
Average Salary: $118,868
Typically, a data architect’s duties include designing analytics applications for numerous platforms and ensuring data solutions are created for performance. Master’s courses not only teach them how to design and develop new database systems but also work to improve the efficiency and usefulness of existing systems. Moreover, they ensure that database administrators and analysts have access to the data they need.
Average Salary: $92,013
Business intelligence (BI) engineers typically create plans to help business users locate the data they need more quickly. They are data experts who employ BI technologies or create bespoke BI analytic solutions for their clients and customers.
Average Salary: $69,517
Regular duties include cleaning, sorting, and formatting massive amounts of data so that it can be analysed effectively. In many businesses, this position also entails keeping tabs on web analytics and conducting A/B tests. In addition to analysing data, decision-makers benefit from data analysts’ reports that clearly articulate the patterns and insights that emerged from their examination of the data.
Suppose you are interested in entering the profession of data science. In that case, you can do a variety of things to get yourself ready for the complex and fascinating opportunities that are available in this industry. You will need to demonstrate your skills and previous work experience to impress potential employers, which is the most crucial thing you can do. Additionally, you can build such abilities and experiences by enrolling in an advanced degree program in the subject that most interests you.