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Data Science in Industry: How to Build Your Career

31 de January 11 min. de leitura

Career in data science

Data Science in Industry: How to Build Your Career

A new horizon of possibilities has become a frequent and unanimous topic in discussions about the future of the industry: how to use the billions of data generated every day, by machines and sensors, to extract even more value and performance from the factory floor. This discussion involves several issues, such as increasing performance, conscious use of natural resources to increase sustainability levels, improving the decision-making process, and allowing intelligent investment in research and development. The key professional in this context is relatively new but essential: the data scientist.

For this culture to materialize, including in the industrial environment, different fronts of professionals focused on data emerge, and careers are on the rise, given the great competitiveness and search for innovation in different sectors of the market.

According to a study by Forbes magazine (2023), technologies such as big data, cloud computing, and artificial intelligence are those with the greatest adoption, across all business sectors, in emerging and developed countries. In numbers, around 75% of corporations plan to incorporate them in the next 5 years. Additionally, jobs for data analysts and scientists, big data, AI and machine learning specialists, and cybersecurity professionals are expected to grow by an average of 30% through 2027.

Career in data science

What is data science?

Data science is an interdisciplinary area that uses different tools to identify patterns and gain insights from raw data collected from different sources, whether from machines or people. This process includes the capture, processing, transformation, and analysis of this information.

In an industrial context, data from the production line – which until now has not been integrated – such as energy consumption, manufacturing time and quantity, or information from active machines, can be interconnected and classified to facilitate strategic decision-making for the business and generate savings in different areas.

Understand how an applied data science solution brings benefits to the industry here.

Career in data science

Professions within the area of data science

Within the area of data science, there are several subdivisions in which professionals can choose to specialize. I’m sharing the main ramifications, necessary in the industrial and other sectors, below.

– Data Engineer:

The professional in this area is responsible for creating and implementing the system that extracts data from various sources. Furthermore, it performs the necessary processing and makes the information available in an orderly and useful way for it to be consumed by analysts and data scientists.

Therefore, the main focus of this segment is on how to structure the database, in addition to being responsible for ensuring good data protection practices and compliance with laws such as LGPD by the industry.

– Data analyst:

The data analyst is the one who performs the diagnosis and has significant insights from the information that is collected. The professional analyzes and interprets the data, and understands the behavior patterns of the investigated problem. To do this, they also need to understand the business context in which the failure is inserted, in addition to understanding the reasons behind the procedures found. Finally, he is usually responsible for creating dashboards, where the graphical and dynamic visualization of data is made.

– Data Scientist:

These professionals are characterized by a strategic, mathematical, and analytical vision. This is because it is their role to study behavior and understand the predictive probabilities of the consequence of the data in question. This is reflected in the industrial environment, or any other sector, in the sense of contributing to ensuring that the decisions made are aligned with the purpose of the business, and can, for example, guide it towards being more productive and sustainable. Therefore, they are the ones who ask the correct questions to the data, using the answers to understand patterns, so they can pass demands on to other professionals, in search of information that will be used as a basis for event predictions.

– Business Intelligence Analyst:

Professionals in this area focus on the business. Its main objective is to find and implement competitive advantages through classification and monitoring of results within and outside the industry. They develop reports, monitor market trends, and work together with data scientists to suggest strategies and optimizations.

– Machine Learning Engineer

The machine learning engineer is responsible for creating and implementing machine learning models. Your role includes taking machine learning models developed by data scientists and ensuring that they are implemented effectively in production.

Career in data science


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