What is a data scientist and what do they do?
In the current era of global communication and a digital world increasingly moving toward data-driven models, the role of the ‘data scientist’ is becoming one of the most in-demand profiles. Do you want to know what a data scientist is and how to train for one of the professions with the highest employability rates today? We’ll tell you!
In October 2012, 21 years ago, the prestigious publication Harvard Business Review highlighted a professional figure that, at the time, was completely unknown: the data scientist. It was already defined then as “the sexiest job of the 21st century,” and over the past two decades, awareness of what a data scientist is has grown significantly. Today, this role accounts for a large number of job offers on specialized portals and through HR consultancies. If you are wondering what this job consists of and what tasks it involves, keep reading—we explain it in detail.
Data science: what is it?
This field focuses on translating, making sense of, and extracting information from the massive volumes of data generated today. In other words, data science experts aim to provide answers and make predictions by interpreting what is known as Big Data. It is a discipline that combines statistics and mathematics, advanced analytics, specialized programming, and is closely related to data science and artificial intelligence. The process involves collecting information through different systems and methodologies, storing the obtained resources, analyzing them, and translating and interpreting them so that the resulting reports can be used by business analysts and decision-makers within a company.
What is a data scientist?
Data scientists are professionals with training in mathematics, statistics, and programming. For those wondering what a data scientist does, the answer is: they are professionals who collect, extract, and process relevant information coming from different channels and sources. This data may initially seem unrelated, but once analyzed and connected, it leads to insights and conclusions that are highly valuable depending on the industry they are applied to.
The society we live in—constantly connected and evolving—generates data at an extremely fast pace. Companies that understand the value of translating this information are achieving great results through data science. From finance to retail, food, or tourism, organizations use data to make forecasts, such as predicting consumption trends and adapting their products and services to their target audience.
This demand for professionals makes it a field with high employability, as the labor market cannot fully meet the demand for data scientists. According to Glassdoor, which collects anonymous salary reports, a data scientist in Spain earns an average of €34,000 per year (2021).
What does a data scientist do?
Data scientists are one of the key professions for the present and future. A Deloitte and Infoempleo report includes them among the most important roles in the medium and long term. Their main tasks include:
- Collecting data from different sources and documentation systems.
- Cleaning and processing data to remove irrelevant information depending on the company’s objectives.
- Using specialized software for analysis and statistics to generate reports with insights, descriptions, and predictions.
Relationship between data science and artificial intelligence
It is important to highlight the relationship between data science and artificial intelligence (AI). How are they connected? How do they influence each other in a data scientist’s work? Several points clarify this:
- They share common ground. They complement each other but are not the same.
- Data science collects, analyzes, and interprets existing data so companies can improve processes, products, and services.
- Artificial intelligence enables machines to replicate human cognitive processes, with strong predictive capabilities.
AI relies on data to generate algorithms and responses. Data science provides this data to AI systems. In turn, AI supports data science with techniques such as machine learning.
How to become a data scientist
There is no single educational path to become a data scientist. Most professionals come from degrees in mathematics or computer science. This is the foundation.
To advance in this field, it is recommended to pursue specialized postgraduate programs or master’s degrees in data analytics, such as:
- The most focused program is the Master in Big Data Analytics, which teaches key programming languages and data architecture technologies. It also combines technical knowledge with practical case studies and soft skills such as leadership and team management.
At EAE Business School Barcelona, the Master in Big Data Analytics integrates technical knowledge with soft skills such as leadership and team management.
- A broader program is the Master in Business Analytics and Data Strategy, which offers a “technology-adapted development” program and provides students with a “global and strategic vision of analytics implementation” in companies. It combines online learning with a residential period at EAE Barcelona.
Data science is also covered in other specialization programs. The Master in Management STEM includes a module in Business Analytics & Data Science, allowing graduates to deepen their knowledge of this emerging profession and understand how data analytics contributes to business intelligence across all industries.
