8 High-Paying Data Science Jobs That Will Rise to Prominence

Which data science jobs will be most in demand? Here’s a look at the most coveted, top eight job roles from the world of data science.

Data Science has emerged as the most sought-after career of the 21st century. Data Science is now impacting almost every walk of life in every industry. This article describes 7 high-in-demand job roles and the necessary skill sets to command those coveted job roles.

1. Data scientist

A data scientist is a key person who designs the entire data modeling process and designs the models and algorithms required for making predictions and inferencing using the data. Data scientists must understand business challenges and offer the best solutions using data analysis and data processing. They also need to identify trends and patterns that can help the companies make better decisions

Desired Qualifications

Computer Scientist with expertise in Machine Learning & AI. Usually, a Postgraduate degree is desired. A person with a postgraduate or higher degree in Mathematics or statistics can also excel as a data scientist.

Skill Sets

Knowledge of machine learning algorithms, Programming in R / Matlab / Python, Knowledge of Database systems.

2. Data Analyst

A data analyst manipulates large data sets and uses them to identify trends and derive conclusions that can be useful for strategic business decisions. Data analysts deal with massive amounts of data, which requires knowledge of tools and techniques of data compartmentalization & visualization. They also have to perform queries on the databases from time to time. They need to develop algorithms/techniques for efficiently retrieving data from large structured and unstructured databases.

Desired Qualifications

Graduate in Computer Science & Engineering with good knowledge of database systems.

Skill Sets

Knowledge of database systems, Oracle, MySQL, NoSQL, MongoDB, etc. SQL Query language, Matlab / R / Python programming.

3. Data Engineer

Data engineers are responsible for designing, building, and maintaining data pipelines. They clean, aggregate, and organize data from disparate sources and transfer it to data warehouses. In addition, data engineers are responsible for building and maintaining scalable Big Data ecosystems for businesses so that the data scientists can run their algorithms on data systems that are stable and highly optimized. Data engineers also work on batch processing collected data and matching its format to the stored data.

Desired Qualifications

Graduate in Computer Science & Engineering with good knowledge of traditional database systems and extensive data systems or distributed databases.

Skill Sets

Knowledge of database systems, Oracle, MySQL, NoSQL, MongoDB, etc., distributed databases, e.g., Hadoop. In addition, hands-on experience in Hive, R, Ruby, Java, C++, and Matlab would be an advantage.

4. Business Intelligence Specialists

Business intelligence specialists are responsible for developing processes and strategies that help businesses make intelligent decisions based on the data. Business intelligence specialist jobs are often broken down into two categories, Business Intelligence Developers and Business Analysts.

Business Intelligence Developers — also called BI Developers — are in charge of designing and developing strategies that allow business users to find the information they need to make decisions quickly and efficiently. 

Aside from that, they also need to be very comfortable using new BI tools or designing custom ones that provide analytic and business insights to understand their systems better.

BI Developers’ work is primarily business-oriented; they need to have at least a basic understanding of the fundamentals of business models and how they are implemented.

The role of business analysts is slightly different. While they do have a good understanding of how data-oriented technologies work and how to handle large volumes of data, their core responsibility is to identify how Big Data can be linked to actionable business insights for business growth.

Desired Qualifications

Graduate in Information Technology, preferably with a Post Graduate degree in Management.

Skill Sets

Knowledge of Data Analysis tools like SAS and Tableau are preferred. DB/DBA and Data Analysis background is also sought.

5. Data architect

Design, create and manage an organization’s data architecture. A data architect creates the blueprints for data management to easily integrate databases that can be centralized and protected with the best security measures. They also ensure that the data engineers have the best tools and systems to work with.

Desired Qualifications

Graduate in Computer Engineering, preferably with good knowledge of Database systems and Data warehouse.

Skill Sets 
Data warehousing and big data tools like Hive, Pig, and Spark are preferred. Programming Skills like SQL, Python, and Java, and Data Modelling are also essential.

6. Database Administrator

The database administrator is responsible for the proper functioning of all the databases of an enterprise and grants or revokes its services to the company’s employees depending on their requirements. They are also responsible for database backups and recoveries.

Desired Qualifications

Diploma or graduate in Computer Engineering or Information Engineering, preferably with certification in database administration.

Skill Sets

Knowledge of one or more proprietary database systems, e.g., Oracle, MySQL, etc. Experience in database technologies & processes is also necessary. 

7. Machine Learning Engineer 

Machine Learning Engineers are responsible for developing intelligent techniques to perform inference and prediction from the data. In addition, machine learning Engineers work with data scientists and business intelligence specialists to identify decision-making requiring computational intelligence and develop machine learning techniques. As a result, machine Learning Engineers often double as data scientists and vice versa.

Desired Qualifications

Post Graduate in Computer Engineering with specialization in Machine Learning. The candidates should be well versed in foundational data science skills. 

Skill Sets 
Strong knowledge of computer Algorithms and programming skills is necessary. Proficiency in more than one programming language (preferably Python) and sound understanding of Deep Learning and Machine Learning.

8. Statistician

Statistics is the origin of the field of data science. Therefore, sound knowledge of statistics is the most fundamental requirement to develop a career in data science. A statistician not only extracts and offers valuable insights from the data clusters but also helps create new methodologies for the engineers to apply.

Desired Qualifications

Post-graduation or Ph. D. in statistics. Candidates should either have a bachelor’s degree or master’s degree, which provides a good foundation in mathematics/ statistics/ computer science/ economics/ econometrics/ material science.

Skill Sets 
Knowledge of statistical processing tools and methods like predictive modeling, data mining, or parametric estimation is preferred. 

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