Are you interested in a career in data science? This is the best time ever to pursue this career track. The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. The average data scientist earns over $108,000 a year.
The interdisciplinary field of data science involves using processes, algorithms, and systems to extract knowledge and insights from both structured and unstructured data and then applying the knowledge gained from that data across a wide range of applications.
While much data science work is starting to become automated, there is still a high demand for data science professionals. There are a lot of great reasons to consider a career track in data science, but you have to know what paths are available. Experts in data science are needed in all kinds of industries, from companies developing dating apps to government security.
Businesses and organizations of all kinds rely on big data to find solutions to problems and provide better services, so there are lots of different types of careers you could pursue with a degree in data science.
If you are planning on getting a data science degree, here are nine careers that you could consider after graduation.
1. Data Scientist
Armed with a Master of Data Science, which you can study either online or at a traditional educational establishment, you could pursue a career as a data scientist.
In the role, you would find, clean, and organize data on behalf of an organization.
You would need to have the skills to analyze large amounts of complex data and find patterns that would benefit the business or organization you work for. The organization can then come up with effective and strategic decisions.
2. Data Engineer
In this role, you would perform batch processing or real-time processing on data that has been collected and stored. As a data engineer, you could also build and maintain data pipelines that create an interconnected data ecosystem that makes information available to data scientists.
3. Machine Learning Engineer
As a machine learning engineer, you would create data funnels and deliver software solutions. To work in this field, you will need strong programming and statistics skills and excellent knowledge of software engineering.
As well as designing and building machine learning systems, you could be responsible for running tests and monitoring the functionality and performance of systems.
Check out these machine learning interview questions so that, after graduation, you can land the ideal job.
4. Data Architect
The typical duties and responsibilities of a data architect include ensuring data solutions are built for design analytics and performance across numerous platforms.
The role could also involve finding ways to improve the functionality and performance of existing systems and providing access to database analysts and administrators.
5. Machine Learning Scientist
Working as a machine learning scientist, you would research new data approaches and algorithms that can be used in adaptive systems, utilizing supervised, unsupervised, and deep learning methods.
6. Business Intelligence Developer
A career in business intelligence development would involve designing and developing strategies that can assist users in quickly finding relevant information that can help them make better business decisions.
You will need to have a broad range of data expertise to work as a business intelligence developer.
7. Data Analyst
You would transform and manipulate large data sets to meet the desired analysis for businesses, working as a data analyst.
Your duties and responsibilities could include tracking web analytics, analyzing A/B testing, and preparing reports for organizational leaders that effectively communicate the insights and trends found from your analysis.
8. Enterprise Architect
The main duty of an enterprise architect is to align an organization’s strategy with the right technology to execute the required objectives.
That means enterprise architects must have a full understanding of the specific businesses they work for in order to design the systems architecture that meets those needs.
9. Applications Architect
As an applications architect, you would track the behavior of applications that are used within a business or organization and discover how those applications interact with each other and how users interact with them.
You would also focus on designing the architecture of applications, which would include building elements like the infrastructure and user interface.