Career Insights: Top 10 Job Opportunities After Acquiring Bachelor’s Degree in Data Science

Here’s the list of top 10 job opportunities for candidates having a bachelor’s degree in data science

Data science

Data science

Data science has critical applications across most industries. It is one of the fastest-growing and most in-demand careers today. Data science professionals are needed across many industries. Job openings are surging because businesses are producing useful data in expanding volumes. This article lists the top job opportunities after completing a bachelor’s degree in data science. 

 

Data scientists 

Data scientists are employed across many industries, including large companies and government agencies. There is a huge demand for these professionals. As a data scientist, you examine Data science to achieve insights and present these insights to other professionals. Data scientists need to have skills in areas such as computer science, analytics, statistics, modeling, and maths. Depending on your organization and its goals, you may also need a reasonable or high degree of business knowledge and sense.

 

Data Architect

With a data science bachelor’s degree you can become a data architect. The work of a data architect is to ensure data solutions that are built for performance and design analytics applications for multiple platforms. In addition to creating new database systems, data architects often find ways to improve the performance and functionality of existing systems, as well as working to provide access to database administrators and analysts.

 

Data Engineer

The work of a data engineer is to perform batch processing or real-time processing on gathered and stored data. Data engineers are also responsible for building and maintaining data pipelines that create a robust and interconnected data ecosystem within an organization, making information accessible for data scientists.

 

Data Analyst

As a data analyst, your responsibilities include not only the analysis of data but its interpretation as well. This combination of skills makes you indispensable to organizations in their decision-making processes. Employers hire data analysts to find new opportunities for increasing revenue and driving down costs.

 

Statistician

Statisticians work to collect, analyze, and interpret Data science to identify trends and relationships which can be used to inform organizational decision-making. Additionally, the daily responsibilities of statisticians often include design data collection processes, communicating findings to stakeholders, and advising organizational strategy.

 

Data manager 

Data managers must have a much greater awareness of the business side of things than data scientists. They are key to the achievement of important business goals, and they’re responsible for data science flow, processes, and even people coordination wherever relevant. A data manager is responsible for the data of a domain, or perhaps of an entire department or enterprise. You must ensure data integrity throughout the lifecycle, making sure that people who need to use the data can access it efficiently.

 

Data Modeller

The work of the data modeler is essential for data scientists to be able to do their work. Data modelers build the blueprints for databases. These databases are the storage places for the data used by data scientists. Like data scientists, data modelers are essential for a business to gain useful information from raw data science and then use this information for business decisions.

 

Clinical Data Manager

A career as a clinical data manager is the perfect way to combine the experience and expertise that you have in both the IT and health care arenas. As a clinical data manager, you deal with every part of the collection and dissemination of data science. You’ll probably have a leadership role in decision-making when determining the methods that will be used for data collection. Project management and a variety of technical duties will be significant parts of your job.

 

Machine Learning Engineer

Machine learning engineers create data funnels and deliver software solutions. They typically need strong statistics and programming skills, as well as a knowledge of software engineering. In addition to designing and building machine learning systems, they are also responsible for running tests and experiments to monitor the performance and functionality of such systems.

 

Business Intelligence (BI) Developer

BI developers design and develop strategies to assist business users in quickly finding the information they need to make better business decisions. Extremely data science -savvy, they use BI tools or develop custom BI analytic applications to facilitate the end-user’s understanding of their systems.