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AI Automation Index
Analyze the automation vulnerability, task-level AI risk, salary, and demand projection for Data Scientists. Run the upskilling simulator.
AI Vulnerability
Median Salary
Growth Demand
We parsed O*NET's 16 constituent tasks for this occupation and classified them by AI threat risk.
Automate your routine tasks and design your day around strategic advisory to future-proof this score.
Simulate Upskilling →Analyze, manipulate, or process large sets of data using statistical software.
Semi-structured cognitive task involving analysis, inspection, or monitoring.
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
Semi-structured task combining routine and non-routine responsibilities.
Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
Semi-structured task combining routine and non-routine responsibilities.
Clean and manipulate raw data using statistical software.
Semi-structured task combining routine and non-routine responsibilities.
Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
Semi-structured task combining routine and non-routine responsibilities.
Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Design surveys, opinion polls, or other instruments to collect data.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Identify business problems or management objectives that can be addressed through data analysis.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Identify relationships and trends or any factors that could affect the results of research.
Semi-structured task combining routine and non-routine responsibilities.
Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
Semi-structured task combining routine and non-routine responsibilities.
Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
Semi-structured task combining routine and non-routine responsibilities.
Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Recommend data-driven solutions to key stakeholders.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.
Write new functions or applications in programming languages to conduct analyses.
Software coding, programming, or application development task highly susceptible to automated generation.
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<script src="https://giniloh.com/embed.js" async></script> Community Sentiment
Do you agree with the AI automation risk score calculated for this occupation?
O*NET Methodology
This page dynamically extracts data structures sponsored by the U.S. Department of Labor. Our AI classification applies cognitive task automation risk models to individual tasks.
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