Top Data Science Job Roles for Tech Aspirants in 2021 and Beyond

Launch yourself into the world of data science with these valuable job roles.

Data science is an invaluable business asset and organizations across all industries and countries are looking to employ expert data science professionals to take their business forward. With massive amounts of data being produced every day by people, companies can benefit by extracting insights out of the data for smart business decisions. This is where data science comes into play. Only a data scientist can figure out the business challenge and find the right solutions to evade the issue successfully. With an efficient team of data scientists, organizations can avail the competitive edge for innovation and market reputation.

If you are a job aspirant looking to launch yourself in the tech field, data science careers offer high-paying jobs and room to grow further in the field. In 2021 and beyond, the following are the top data science job roles.

1. Data Analyst

A data analyst's job entails many tasks like visualization, processing large amounts of data, and perform queries on databases. To become a data analyst, aspirants have to ace optimization to create and modify algorithms that can be used to cull information from massive databases without corrupting the data. To become a data analyst in 2022, certifications in SQL, R, SAS, and Python are necessary.

2. Data Engineers

Data Engineers are responsible for building and testing scalable big data ecosystems for businesses. For that, data engineers update the existing systems with new versions of the currency technologies to improve the efficiency of the database. Data Engineers require hands-on experience in Hive, NoSQL, R, Ruby, Java, C++, and Matlab.

3. Database Administrator

Database administrators check the proper functioning of all the databases of an organization. They can also grant and revoke its services depending on the requirement. An essential skill to become a database administrator is to know how to backup and recover databases, data security, data modeling, and design.

4. Machine Learning Engineer

Machine learning engineer is a high-demand job profile. These professionals need to have an in-depth knowledge of SQL, REST APIs, and more. Machine learning Engineers also perform A/B testing, built data pipelines, and implement common ML algorithms like classification, clustering, etc. Along with the technical knowledge, having a strong mathematical and statistical foundation is also imperative.

5. Data Scientist

A data scientist plays a vital role in the business setup. He/she is responsible to understand the business challenges and offer the best solution using data analysis and data processing. The aspirants are expected to run predictive analysis and analyze unstructured data to extract actionable insights. This task requires identifying trends and patterns to make better decisions. The required skills to become a data scientist are R, MatLab, SQL, and Python, with an advanced degree in mathematics or computer engineering.

6. Data Architect

Data Architects are responsible to create blueprints for data management for databases to be easily integrated, centralized, and protected with tight security. This job profile needs expert knowledge in data warehousing, data modeling, extraction transformation, along with Hive, Pig, and Spark.

7. Statistician

As the name suggests, a statistician needs to have an expert understanding of statistical theories and data organization. Statisticians don't just extract insights from data clusters, they also help create new techniques to help engineers. All the tasks require logic and database systems like SQL and ML technologies like data mining.

8. Business Analyst

A business analyst holds a unique position in all data science-related jobs. Along with a good understanding of how data technologies work and how to handle massive volumes of data, a business analyst has to identify high-value data from low-value data to grow the business. These professionals act as a link between data engineers and management executives, which requires them to have business finance and business intelligence skills.

9. Data and Analytics Manager

This professional is responsible to check the data science operations and assign the duties according to team skills and expertise. To become data and analytics managers, candidates need to have excellent social and leadership skills, unique thinking, and knowledge of data science technologies like Python, SAS, R, and Java.