What Are the Different Types of Information Scientist Jobs?

A data scientist is an engineer or expert who can use scientific methods and use data mining tools to digitally reproduce and recognize information such as complex numbers, symbols, text, web addresses, audio or video, and can find new data insights (different To statisticians or analysts). A good data scientist needs to have the following qualities: understanding data collection, mathematical algorithms, mathematical software, data analysis, predictive analysis, market applications, and decision analysis.

Data scientist

discuss

A data scientist is an engineer or expert who can use scientific methods and use data mining tools to digitally reproduce and recognize information such as complex numbers, symbols, text, web addresses, audio or video, and can find new data insights (different To statisticians or analysts). A good data scientist needs to have the following qualities: understanding data collection, mathematical algorithms, mathematical software, data analysis, predictive analysis, market applications, and decision analysis.

Chinese name

Data scientist

Foreign name

Datician / Daticist / Data scientist

The "data scientist" was first proposed by Natahn Yau in 2009. Its concept is an engineer who uses scientific methods and uses data mining tools to find new data insights. Data scientists combine the roles of technical experts and quantitative analysts. Compared with traditional quantitative analysts, the latter usually uses the company's internal data for analysis to support leadership decisions; the former is more focused on user-oriented Data to create products and processes with different characteristics and provide customers with meaningful value-added services. ^[1]

The customer-oriented nature determines the majority of data scientists to hold positions in the company's product development or marketing department or to serve as chief technology officer. So what core competencies do data scientists need? Tech journalist Derrick Harris describes in his article some of the skills a data scientist should have.

He said that when you ask others what a data scientist is or what a data scientist is, it is easy to find that "data scientist" is actually formed from the term confusion caused by "big data". The core competencies of data science are defined as: SQL, statistics, predictive modeling and programming, Python, etc. These sound reasonable. But soon more terms were added to it: Hadoop / MapReduce, machine learning, visualization, and even traditional math, physics, computer science and similar capabilities.

Many have called for professionalism, business intelligence, creativity, and expressiveness to be just as important. A data scientist must not only be good at numbers (such people are called statisticians or analysts), but also be able to understand the business: what kind of data or results are informative; being able to find new data sets and make them Create new products; then enable CEOs to understand it all. This is a difficult task, and there are very few people in this world. As top data scientists, they are not required to make any positive changes to the environment, but they need to try to do something really advanced to help everyone better solve business problems.

Six capabilities of a data scientist:

1. The ability to extract and synthesize data;

2. Statistical analysis ability;

3. Data insight and information mining capabilities;

4. Develop software capabilities;

5. Network programming ability;

6. Visual representation of data.

Data scientists involve disciplines:

1. Computer science: data acquisition, data analysis, data storage, and data security

2. Mathematical statistics: data analysis, data filtering, data mining, and data optimization

3. Graphic design: display data results, such as expressing data into three-dimensional graphics for better understanding and use

4. Human-Computer Interaction: Establish an organic connection between users and data, making it easier for people to use data