Working with data and systems, making sense of data, and conveying research conclusions into terms that others can comprehend are all common tasks in today’s finest employment. You may get ready for these careers by taking data science classes or by pursuing a master’s in data science.
Analysts, researchers, programmers, modelers, and data engineers—technical people who understand data and systems—are in high demand. Database administrators, technical team leaders, and IT professionals—managers who understand business objectives and can transform research findings into information to aid decision-making—are in high demand.
7 Career Paths To Select After Mastering In Data Science & Big Data
There are multiple types of career paths available that you can pursue after completing your data science course. Hence every student has different types of affections for subjects. But apart from your passion for the topic you also have to know which are the highest paying jobs.
Here are seven types of different career selections for you, which you can pursue after mastering Data Science and big data.
1. Statistician
Employed by:
Governments at all levels, municipal governments, consultancy and reporting firms, market research firms, and research institutions are all involved in data science.
Responsibilities:
- Collect, organize, and evaluate data to provide valuable insights, trends, and solutions.
- Examine the data for quality and correctness.
- Create and test novel data collecting techniques and procedures.
- This career path can also be pursued by pursuing a Master’s in Statistics.
2. Business Intelligence (BI) Analyst
Employed by:
Companies in the fields of technology, finance, consulting and reporting. Business analysis jobs are associated with the present and the future perspective of the business.
Tasks:
- The cross-departmental collaboration operations become perfect.
- Make presentations about the company’s statistics trends, along with future directions.
- Organize business seminars and workshops. Then assist the managers to comprehend the business intelligence.
- You may also pursue this career path by enrolling in a Master’s degree program in Data Science and Business Intelligence.
3. Data Analyst
Employed by:
The data science and analysis companies in the telecommunications, finance, manufacturing, construction, and utility industries, as well as other significant corporations.
Responsibilities:
- Collect and analyze data that is pertinent to the client’s requirements
- New data sources and data gathering methods are tested and evaluated.
- Analyze data and provide conclusions in the form of graphs or reports.
4. Big Data Engineer
Employed by:
Companies in the fields of technology, entertainment, retail, and trade.
Tasks:
- Create, test, and manage data science, Big Data tools, and infrastructure.
- Monitor and assist the performance, as well it advises the infrastructure modifications.
- Portray your company data retention policy.
5. Database Administrator (DBA)
Employed by:
Institutions such as financial and medical institutions, social media corporations, research institutes, and legal firms, to name a few. All of these companies are working in data science.
Responsibilities:
- Database systems must be installed, configured, and monitored.
- Keep an eye on the company’s servers and make sure they’re running well.
- To secure data protection, collaborate with cybersecurity professionals.
6. Data Architect
Employed by:
Education institutions, healthcare facilities, and other public or private organizations
Responsibilities:
- Data and database design, organization, and upkeep
- Ensure that the data obtained is genuine and accurate.
- Create a data strategy with the help of other departments inside the firm.
7. Machine Learning Engineer
Employed by:
Amazon, Apple, Microsoft, Accenture, Autodesk, and other significant worldwide corporations
Tasks:
- Create, test, and improve self-running and self-learning software.
- It helps the Data Science team become more efficient by collaborating with them.
- Assists in the scaling, maintenance, and debugging of the code.
The best machine learning courses can help students work efficiently in this role.
Conclusion
Raw data is given meaning by data science, which transforms information into actionable insights that may be utilized to expand a business and spot market trends. Data Science has become a profitable job due to a scarcity of skilled Data Scientists and high demand.
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