The modern world is filled with a huge amount of data, and its analysis is becoming a key factor for successful business and science. So how do you get information from a lot of data to help you make the right decisions? To solve this problem, at the intersection of data analytics and programming a new profession has emerged – Data Scientist. In this article, I will explain in detail what Data Science is and how to enter this profession, what technical and creative skills are needed to work in this field.
The Data Scientist Profession
The Data Scientist profession emerged in early ~ 2008, when large companies began to recruit analysts to work with large volumes of data. These professionals were not only directly involved in analysis, but also used programming skills in their work. Since then, the profession has become increasingly popular and in demand. Today, a Data Scientist is a professional who uses data analysis, programming, and machine learning to provide information to help make decisions and predictions.
What is Data Science and who is a Data Scientist
Data Science is a science of data that combines statistics, mathematical modeling, programming, and subject matter expertise. A Data Scientist is a professional who uses Data Science methods to solve problems in various fields, such as marketing, banking, medicine, science, etc.
Examples of the use of Data Science:
- Analysis of the customer base to identify trends in their behavior and predict future sales.
- Analysis of medical data to find new treatments and optimize treatment processes.
- Analysis of financial data to prevent losses.
What is the difference between Data Science and Data Analytics
Data Science and Data Analytics are two different fields, although related. Data Analytics is the analysis of data to obtain information to help make decisions. However, Data Science includes a broader range of knowledge and skills, such as programming, statistics, and mathematical modeling.
How much a Data Scientist can earn
Data Science is one of the highest paying professions in IT, and Data Scientist salaries depend on many factors, including experience, education level, company, and location. The average Data Scientist salary is around $113,000 per year, with starting salaries that can be around $85,000, and the highest paid professionals can earn over $160,000 per year or more. In Russia, the average salary starts at 90,000 rubles and can reach 300,000 rubles a year.
Forecasts for the future also promise further growth in demand for Data Scientist and an increase in salaries. In the coming years, the field of Data Science is predicted to grow at a rate of over 28% a year, so demand for specialists in this field will remain high.
Technical Skills for Data Science
Statistics and mathematical modeling
Statistics and mathematical modeling are key skills for working in Data Science. You need to be able to work with large amounts of data and analyze it using various statistical methods and mathematical models.
For example, a Data Scientist can use linear regression techniques to build models that predict future results, as well as clustering techniques to group data by similarity.
Programming in Python
Python is one of the main programming languages used in Data Science. A Data Scientist must be able to work with data using Python libraries such as NumPy, Pandas, and Matplotlib, as well as be able to create and process machine learning algorithms in Python.
SQL and working with databases
SQL (Structured Query Language) is a programming language used to manage relational databases. It allows you to create, modify and delete tables, as well as query the database to retrieve the necessary information. For example, customer, sales, and transaction data may be stored in a database, and to work with this data, Data Scientists need to know how to run SQL queries.
Creative Skills for Data Science
To work in Data Science, it is not enough just to know a couple of formulas and be able to count the coefficients. You need additional creative intellectual skills to help you choose the right model and interpret the results.
Understanding the nature of the data
It is worth paying attention to the context and meaning of the data: what data you have, where it comes from, how the data is related to each other, and what information it contains. The first step is always to examine the structure of the available data sources and understand the meaning of the problem. Then there is the selection of optimal models, the development of hypotheses, and experimentation. And in the end you have to analyze the data and draw conclusions.
It is important to be able to present the results beautifully in a colorful report, a compelling presentation, a dynamic website, or a sharp video. The main visualization tools are plotly, matplotlib, seaborn, and Tableau and Power BI.
Communicating your ideas
In addition to technical skills and understanding of data, communication skills are essential to working in Data Science. A Data Scientist must be able to explain his or her ideas and results to the team, management, and customers.
This is important to make data understandable to people who are not experts in the field. Developing communication skills helps Data Scientists work effectively as part of a team and achieve common goals.
The Future of the Data Scientist Profession
Data Science is a profession that combines knowledge of mathematics, statistics, and programming, as well as creativity and communication skills. It is a profession of the future that is becoming more and more relevant and in demand in business and science, and its importance will only grow.
How to become a Data Scientist
If you are interested in the Data Scientist profession and want to learn it, there are many ways to get the right knowledge and skills. You need to be able to program, know statistical methods, work with databases, and be able to understand the essence of data, visualize it and communicate your ideas.
You can take specialized courses and training, get an advanced degree in mathematics, statistics or computer science, or learn the necessary programming languages and data analysis tools on your own.
There are many ways to become a Data Scientist, but the most important thing is the desire to learn and understand data and use modern computer technology.