Data Scientists
Additional Information
Duties
Data scientists generally perform the following tasks:
- Identify available and relevant data for the project
- Collect, organize, and analyze data
- Develop, test, and update algorithms and models
- Use data visualization tools to present their findings
- Make business recommendations to stakeholders based on their analysis
Typically, data scientists start a project by gathering or identifying the necessary data sources, such as surveys. They use various methods to obtain data, including accessing other organizations’ databases or employing web-scraping tools (software that extracts specific information from websites). They often begin with large, unstructured datasets known as raw data. To analyze this data properly, they must "clean" it, which involves structuring the data so it can be processed by software programs.
Data scientists create algorithms (instructions that tell computers what to do) and models to support machine learning programs. They use machine learning to classify or categorize data or to make predictions based on their models. They also test these algorithms and models for accuracy and update them with newly collected data.
Data scientists frequently use data visualization software to display their findings as charts, maps, and other graphics. These visualization techniques enable them to communicate their analyses clearly to both technical and non-technical audiences, including colleagues, managers, and clients. Ensuring that their audience understands the information is crucial for making business recommendations or suggesting process changes based on their analysis.
Some data scientists specialize in certain areas. For example, those with a strong coding or engineering background might develop or recommend systems, build machine learning algorithms, and enhance web-browsing functions. Others conduct research for reports or academic journals. Still others focus on improving business strategies in areas like marketing, sales, and user engagement.
Education
Data scientists generally need at least a bachelor's degree, though some positions require a master's or doctoral degree. Common degrees for this field include mathematics, statistics, computer science, business, and engineering.
Since data science relies heavily on algorithms and statistical techniques, students need a solid foundation in mathematics and statistics. High school students interested in data science should take courses in linear algebra, calculus, and probability and statistics.
In college, courses in computer science are just as crucial as those in math and statistics. Students need to learn data-oriented programming languages and become proficient with statistical, database, and other software used for presenting analyses.
Other Experience
Some employers look for industry-specific experience or education. For instance, data scientists aiming to work in asset management may need finance industry experience or coursework in investments, banking, or related subjects.
Important Qualities
- Analytical skills: Data scientists must excel at researching and interpreting findings.
- Computer skills: Proficiency in coding, data analysis, algorithm development, and using data visualization tools is essential.
- Communication skills: They need to effectively convey their analysis results to both technical and nontechnical audiences to make business recommendations.
- Logical-thinking skills: Understanding and developing statistical models and analyzing data is crucial.
- Math skills: Statistical methods are used to collect and organize data.
- Problem-solving skills: They must devise solutions for issues in data collection, cleaning, and developing statistical models and algorithms.
Pay
In May 2023, the median annual salary for data scientists was $108,020. This means that half of the data scientists earned more than this amount, while the other half earned less. The lowest 10 percent made under $61,070, whereas the highest 10 percent earned over $184,090.
Job Projections
Employment of data scientists is expected to grow by 35 percent from 2022 to 2032, which is significantly faster than the average for all occupations.