Modern organisations rely on data. They gather, analyse, and manipulate vast amounts of information in order to understand their customers better, make processes more efficient, and, ultimately, meet their goals.
Therefore, it’s not surprising that the data sector is booming and data professionals are in short supply.
The data science jobs in high demand include Data Analyst, Data Scientist, Data Engineer, Data Manager, and Business Analyst. Let’s explore these data science careers below.
Top Data Science Jobs in High Demand
Professionals working in data science may have a number of different job titles. You may think that a data analyst, data manager, and data engineer are essentially the same thing, but there are some key differences.
Let’s take a look at the most in-demand roles in the field, and the key differences between each.
Data Analysts work with large volumes of raw data and transform it into a form that can be more easily used. This involves data munging, also called data wrangled, where the analyst turns raw data into another more appropriate format for analysing.
After processing the data, a Data Analyst may also analyse the information and create reports containing recommendations and predicted trends.
Data Scientists take a big-picture approach to data analysis to help companies best use data for optimum results.
They develop data collection and management strategies for organisations, often starting at the beginning of the process by identifying the most useful data collection sources.
From there, a Data Scientist may work to improve data management practices, and use the data to develop recommendations or predict future trends.
Data Engineers work at the back end of the process, creating the infrastructure necessary for Data Scientists to do their work. They build and test Big Data ecosystems that Data Scientists and other data professionals use to analyse and optimise vast amounts of information.
A Data Engineer may build and maintain data pipelines that allow Data Scientists to access information, or could batch process stored data.
This is a managerial role that involves supervising and leading other data science professionals. As such, a Data Manager assigns tasks to team members, oversees workflow, performs quality control, and develops data analytic strategies.
Data Managers need to have a combination of technical knowledge and excellent managerial skills, and must keep up with the latest trends and developments in the industry.
Although this job title doesn’t include the word data, this role is closely related to the world of data science.
Business Analysts form a crucial connection between business and data or IT professionals. A key part of their role is coordinating with business leaders and executives to understand the company’s data needs, as well as communicate potential strategies and approaches.
Business Analysts may also work directly with data sets to improve the company’s products or processes.
How do different data science roles relate to each other?
These distinct data science roles are not designed to replace one another, but rather complement and support each other.
Depending on its size, an organisation may have a large team of data science professionals, with all of the designations mentioned above and more. These professionals work together to optimise data systems and produce the best results.
For example, Data Engineers build and maintain data ecosystems, in order for Data Scientists to develop and execute the best data management practices. Both roles are equally crucial, and a Data Scientist would not be able to do their work without the Data Engineer doing theirs.
Equally, a Data Analyst wouldn’t be able to process large volumes of raw data without the data pipelines that Data Engineers put in place and ensure are working optimally. At the same time, Business Analysts ensure that the Data Analysts’ and Data Scientists’ analysis and strategies will meet the company’s needs.
Finally, a Data Manager supervises the other members of the team, supporting them to work efficiently and effectively.
Emerging Roles in Data Science
Data science is a continually evolving field, and is constantly facing new demands as fresh trends emerge. As such, new, unconventional roles are emerging all the time.
Some of the data science roles to look out for in the future include:
With companies gathering and leveraging increasingly large data sets, this raises more and more ethical issues. Data ethicists are becoming crucial members of the data science team, as they identify potential ethical issues and suggest solutions.
Companies have long recognised the power of storytelling, and these professionals combine persuasive storytelling with strong data insights for strong results.
Data science is very powerful, but it can also be highly technical. Behavioural Psychologists give insight into users’ needs and behaviours, working with Data Scientists to develop better products and processes.
Get Ready for a Successful Career in Data Science
To qualify for data science jobs, you’ll typically need to have a degree in data management, data analytics, or business analytics. EDHEC’s MSc in Data Management & Business Analytics equips you with the skills and knowledge you need to take an active role in business transformation, from managerial decision-making to artificial intelligence.
We also offer an MSc in Business Strategy & Analytics, which teaches future leaders and decision-makers how to develop their strategic thinking and use data insights to build more sustainable, inclusive, and impactful companies.
Both are offered fully online, so they are ideal for busy professionals looking to advance their careers or transition into data science.