Occupation Details
Data Scientists
Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
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Salary & Job Outlook
Starting Salary
$69,090.00
New York StateMedian Salary
$129,080.00
New York StateExperienced Salary
$156,380.00
New York StateNational Average for Comparison
New York State Job Market Outlook
Jobs Right Now (2018)
14,430
professionals in NYFuture Job Growth (2030)
18,990
+456 jobs/yearNew Jobs Every Year
1,545
new opportunities yearlyGrowth Rate
0.3%
projected increasePreparation: Experience, Training, and Education
The list below outlines the prior educational experience required to perform in this occupation.
Degree Needed - Four-year college
Experience Requirements
A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
Education Requirements
Most of these occupations require a four-year bachelor's degree, but some do not.
Training Details
Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.
Transferrable Skills and Experience
Many of these occupations involve coordinating, supervising, managing, or training others. Examples include real estate brokers, sales managers, database administrators, graphic designers, conservation scientists, art directors, and cost estimators.
School Programs
The following lists school programs which are applicable to this occupation.
Licensing & Certification
State License and Certifications Requirements are not currently associated with this occupation.
Apprenticeship
Contact your regional representative to learn more about apprenticeships available in your area by visiting Apprenticeship Contacts.
Skills
Skills information is not available for this occupation.
Knowledge
Knowledge information is not available for this occupation.
Work Environment
Work Environment information is not available for this occupation.
Work Styles
Work styles information is not available for this occupation.
Tools & Technology
This list below describes the machines, equipment, tools, software, and information technology that workers in this occupation will use.
Tools
Tool information is not available for this occupation.
Technology
Technology information is not available for this occupation.
Duties
Job duties information is not available for this occupation.
Tasks
The list below outlines specific tasks that a worker in this occupation is called upon to do regularly.
- Analyze, manipulate, or process large sets of data using statistical software.
- Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
- Clean and manipulate raw data using statistical software.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
- Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
- Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
- Design surveys, opinion polls, or other instruments to collect data.
- Identify business problems or management objectives that can be addressed through data analysis.
- Identify relationships and trends or any factors that could affect the results of research.
- Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
- Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
- Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
- Recommend data-driven solutions to key stakeholders.
- Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
- Write new functions or applications in programming languages to conduct analyses.