Data science is the theory and practice of ideas. It includes big data, predictive analytics, and artificial intelligence. Data science is vital in commerce and business.
It is an honorable job to be able to analyze the market and devise profitable strategies. Employers are looking for professionals who can leverage the data science benefits to their advantage.
It is smart to pursue a career as a data scientist, not just because it is fashionable and lucrative, but because it is the foundation that allows the industry to evolve.
We have listed the 10 best data science jobs that are expected to gain popularity in 2022.
10 Best Data Science Jobs in 2022
1. Data Scientist
A data scientist manages large and complex datasets using machine learning and predictive analysis.
Candidates must be able to develop algorithms that facilitate the collection and cleaning of data to work as Data scientists. Bonus: A degree in statistics, computer science, or mathematics will be helpful!
2. Machine Learning Scientist
A machine learning scientist is required to study new data methods and algorithms for adaptive systems. This includes supervised and unsupervised learning, as well as deep learning.
They are often called research scientists or engineers. A machine learning scientist’s main responsibilities include designing, developing, and experimenting with ML, NLP, computer vision, and solving complex problems.
3. Business Intelligence Developer
These professionals analyze complex databases to determine the most recent market trends and impact business decisions.
BI developers must design, prototype, and manage complex data using cloud-based platforms. Candidates must have a solid understanding of data mining, data warehouse design, and SQL to be able to pursue a career in BI development.
4. Applications Architect
A software architect is responsible for the design and development of a variety of software applications. They work with the internal stakeholders as well as application development teams to monitor and implement application development steps and to document the entire process.
A skilled architect must be proficient in application architecture.
This knowledge can then be applied to optimize business operations.
Candidates should have a bachelor’s degree, in either software engineering or application development, to be considered for the top job.
5. Data Analyst
These individuals are responsible for creating and maintaining data systems and databases, as well as fixing any coding errors. The data analyst interprets data using statistical tools.
They pay particular attention to patterns and trends that can be useful for predictive and diagnostic analytics. An effective data analyst must have leadership skills and analytical skills.
Statisticians work to collect, analyze, and interpret data to identify trends and relationships used to make organizational decision-making.
A statistician’s regular responsibilities include the design of data collection processes, communication with stakeholders, and advice on organizational strategy.
7. Big Data Architect
Big Engineers plan and manage big data environments using Spark and Hadoop. For a career in big data architecture, candidates must be skilled in data mining, data migration, as well as data visualization. They will also be expected to demonstrate their proficiency in Java, Python, and C++.
8. Machine Learning Engineer
They must be able to work with a variety of programming languages and be skilled in AI programming. Machine learning engineers will need to be able to use predictive models and NLP to manage large datasets.
An ML engineer will need to have experience in ML application development and proficiency in programming languages such as Scala, Python, Java.
9. Enterprise Architect
An enterprise administrator will oversee the maintenance and upkeep of the company’s IT services and networks.
They will have to manage, improve, and update enterprise services. They will also be responsible to align an organization’s strategy and the technology required to achieve it.
10. Data Science Manager
This data scientist manager assists organizations in leveraging the data they have collected and works with the data scientists and engineers to provide valuable insight and direction to their management team. Consulting firms, financial institutions, and healthcare organizations are hiring data science managers.
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