Description
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.
Interests
- Investigative
- Conventional
Work Values
Work Styles
Tasks
- 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.
Work Activities
Detailed Work Activities
Technology Skills
- Data base user interface and query software
- Presentation software
- Object or component oriented development software
- Development environment software
- Analytical or scientific software
Skills
Knowledge
Most Common Education Level
The “Most Common Education Level” refers to the level of education held by the majority of workers in a given occupation. For example, if the highest percentage of workers in a role have an Associate’s Degree, that suggests this is the typical educational requirement. Knowing this helps you plan how many years of education you may need to pursue that career.
Certificates
Certificate name
GIAC Machine Learning EngineerCertifying Organization
Global Information Assurance Certification
Type
Core
Certificate name
Data Analytics 1Certifying Organization
Smart Automation Certification Alliance
Type
Product/Equipment
Certificate name
Data Services SpecializationCertifying Organization
Medical Library Association
Type
Core
Income Percentile
The income percentiles show how earnings are distributed within a profession. The 10th percentile means that 10% of workers earned less than that amount. The median (50th percentile) indicates that half of workers earned more, and half earned less. The 90th percentile reflects what the top 10% of earners in the field make.
| Income Percentile | Income |
|---|---|
| Low (10%) | $NaN |
| Median (50%) | $NaN |
| High (90%) | $NaN |
Income by Experience
This table shows how income typically grows with experience—from entry level (0–2 years), to mid-level (3–7 years), to senior level (8+ years).
| Experience | Income |
|---|---|
| Entry Level | $50,000 |
| Mid Level | $100,000 |
| Senior Level | $150,000 |
Employability
There are currently 202,900 jobs in this career path. Over the next 10 years, that number is expected to increase to 276,000 positions, reflecting a projected growth of 36%.
The Projected Job Growth figure refers to the expected increase or decrease in employment within a specific career field over a certain period of time.
Projected Job Growth of 36%
The career information and data on this site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), with ONET® being a registered trademark of USDOL/ETA. Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA; CareerOneStop, sponsored by the U.S. Department of Labor, Employment and Training Administration (DOLETA) and the Minnesota Department of Employment and Economic Development (DEED); and the U.S. Bureau of Labor Statistics (BLS).
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