What Is Data Science?

To get an idea of the importance of this sector, we can mention one of the largest companies today, Amazon, which has been investing increasingly large amounts in the area and in hiring professionals who know how to collect and interpret data.

Today, the increasing use of the internet has opened the door to an enormous amount of raw data available.

The goal of data science is to transform all this material into useful information for companies.

Logistics & Data Science

Logistics is the term used to define the methods used to ship products or services to the customer in an agile and high-quality manner. These methods involve several areas, covering the entire shipping process, from storage to delivery to the customer, as in cases of online purchases, for example. The goal is to ensure that the customer receives the purchased product in ideal conditions and within the stated time frame.

Given the enormous complexity and importance of this process, an increasing number of companies have turned to data science to optimize and improve internal and logistics processes.

Check out some of its applications within logistics below:

• Analysis focused on planning;
• Sales forecasting;
• Optimization of the inventory movement process;
• Process automation, such as picking and packing (preparation and packaging of orders).

Data Science and Distribution Processes

Another major sector that benefits from Data Science is distribution. This is because, through the analysis of this data, it is possible to anticipate flows and, from there, plan in advance the best delivery routes. Routes are defined by data scientists, who, through the integration of information collected during trips, GPS data, and proprietary Big Data algorithms, interpret the information received and define the best route.

Some of the information that can be defined through this analysis includes:

• Frequency of orders;
• Average route speed;
• Quantity of goods;
• Distance between pickup and delivery points.

In addition to a direct improvement in the delivery process, this analysis also generates savings in the commercial relationship with carriers and in internal costs, with lower spending on fuel and vehicle rentals, for example.

How to Become a Data Scientist?

Banks, advertising agencies, market research companies, and industries are some of the sectors that can employ a data scientist, explains Professor Cibele Russo, of the Institute of Mathematical and Computer Sciences (ICMC) at USP in an interview with Jornal da USP. According to her, "there is an enormous market, demanding even more than universities can offer."

All this investment has also generated a great demand for professionals specialized in the area.

The average salary, the level of job satisfaction, and the number of available positions are some of the advantages of the market today. In Brazil, according to the online platform Glassdoor, a data scientist in Brazil can earn between R$6,000 and R$18,000, depending on seniority.

In another survey, conducted by Deloitte Consulting, it was found that 70% of the companies interviewed wanted to hire data scientists, indicating that the market is already aware of how Data Science can impact and transform businesses.

Since there is no specific academic degree in Data Science, this professional can come from areas such as Statistics or Computer Science, and it is common to find professionals from other areas working as Data Scientists (Marketing, Economics, Social Sciences, etc.).

For those thinking about transitioning into the area, knowledge of Data Science will require time and dedication. The training you choose should be a mix of theoretical grounding in programming languages, statistics, and others, in addition to practical applications and experiments. The time needed to start in the career can vary according to the time available for studies.

During this period, it is important to apply the knowledge acquired in a practical way in personal or volunteer projects. They can help with the production of your portfolio and with reinforcing your learning.