So now it's time for you to delve deeper into this subject, let's go:
But what does a data scientist do?
What is the profile of a Data Scientist?
The technical skills a Data Scientist will develop
Everyday tools
Day to day life of a data scientist
Which companies are hiring?
Salaries
Practical Applications
7.1 Behavioral Customer Segmentation (Case: Facebook)
7.2 Recommendation Engine Suggesting Products to Customers
7.3 Marketing Analytics Suggesting New Sales Packages
7.4 Price Optimization
7.5 Funnel Analysis/Prioritization of Potential Customers
7.6 Attribution of Marketing Campaign Models
7.7 Mining Customer Feedback
7.8 Bots for Customer Service (Case: Microsoft)
7.9 Churn Predictions (Case: American Express)
7.10 Routing Optimization
7.11 Inventory Optimization
7.12 Scenario Simulation for Production Lines
7.13 Negotiation Engine for Purchases
7.14 Visualization of Key Metrics
7.15 Improving Products with Artificial Intelligence (Case: Intel)
7.16 Improving Database Architecture
7.17 Employee Attrition Modeling
7.18 Fraud Detection
7.19 Financial Forecasting
But what does a data scientist do?
Have you noticed the enormous amount of france companies email list that is generated today? According to IDC, the digital universe is doubling every two years. In 2013, there were 4.4 trillion gigabytes on the planet. This number is expected to multiply by 10 by 2020.
Every action you take leaves a record of data. The time you spend reading this article, the subject, the movement of your mouse, your location, in short, everything generates information consciously and unconsciously.
And this data is distributed across several databases, which can be used to extract information, generate predictions and initiate automation.
What is the profile of a Data Scientist?
The role of this professional within a company requires a series of characteristics so that he can organize the sea of data and transform it into results.
Analytical
To be able to deal with company data, it is important that you already have a profile that naturally concerns you with information and bases your decisions on it. This is already innate in analytical and pragmatic profiles. Generally, people who are interested in professions related to exact sciences such as engineering, statistics, programming, administration, and mathematics have this profile.
Focus on results
Despite having the term “scientist” in the name, this professional will be working in companies that have objectives and goals to be achieved. Therefore, the profile of this professional needs to clearly show the importance of results and have a nose for business opportunities.
Communication
Even though this professional has a specific profile, he or she will deal with all areas of the company. Therefore, having clear communication and knowing how to listen to everyone will be essential to help you make decisions about which actions to take. This skill will also help when it comes to presenting the results and “selling” data projects to the rest of the company.
The technical skills a Data Scientist will develop
Schedule
Handling and processing data requires programming knowledge. Even with the advancement of technologies that allow data processing in a more intuitive way, such as Excel, Google Sheets and Zapier, there are still several demands that require a deeper knowledge of programming for more complex tasks and applications that use artificial intelligence. Languages such as Python and SQL are the most used among professionals. According to Pietro Oliveira, Data Engineer at EBANX, “languages such as Python already have several libraries that facilitate the work of statistics and data manipulation, such as Pandas and Numpy, which already perform average, median, standard deviation and other statistical metrics with 2 lines of code”.
Mathematics / Statistics
Worse than not knowing the answer is thinking you do. That's why the work of a data scientist requires a lot of accuracy in the information that is passed on, as it can completely change the course of the company. To be able to be assertive, it is essential to understand statistical techniques such as Clustering, Dimensionality Reduction, Latent Variable Analysis, Linear Regression, Causal Effects Analysis, Predictive Modeling, among others.
Business
Data without context means nothing. This is a skill that is highly demanded by Data Scientists. They need to know the entire business chain, from customer generation to after-sales, including the product offered and the company's support areas, such as IT, finance, among others. Only then will it be possible to understand the data generated and know how to interpret it correctly.
Working as the data manager at Madeira Madeira, one of the leading e-commerce companies in Brazil, Rafael Dias demands this skill from his team. According to him, “The main characteristic is someone who is always based on data to make decisions (data driven). They also need to be curious and interested in how the business or the dynamics of the company/institution they are part of works.”
Having knowledge of tools and techniques such as design thinking, business model canvas, personas, strategic planning and value matrix can provide a basis for decisions.
Machine learning / Big data
The complexity of working with more advanced techniques has decreased significantly. Both in terms of processing power, which has increased exponentially, and in terms of access to complex algorithms that can be used by any professional through IBM Watson, Microsoft Bots, and other libraries. Tools such as R Project for statistical computing analysis are also used on a daily basis.
Data processing
The ideal scenario for a data scientist is to arrive in an environment with structured data ready to be analyzed. However, this is not the reality for companies, especially in Brazil, where there is a huge lack of professional data structure. Therefore, the day-to-day work of a data scientist will be very much related to structuring in order to prepare the ground before generating great results. One of the tools most used by data scientists is ETL, which makes it essential to master it.