20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You’ll split time between data collection, cleaning, analysis, and reporting. Morning might mean checking survey responses, fixing data-entry errors in Microsoft Excel, and calibrating instruments if you’re collecting scientific measurements.
Afternoons often go to running analyses in IBM SPSS Statistics, making charts in Microsoft PowerPoint or Excel, and writing short reports in Microsoft Word. You’ll also meet with the team on Microsoft Teams to coordinate recruiters or fieldwork and to decide next steps for sampling or nonresponse issues.
Start with Microsoft Excel — most datasets, summaries, and quick visualizations happen there. Learn pivot tables, sorting, VLOOKUP/XLOOKUP, and basic charts.
Next, learn IBM SPSS Statistics for formal survey analysis (cross-tabs, weighting, significance tests). Also be comfortable with Microsoft Word for proposals and reports, PowerPoint for visual summaries, and Microsoft Teams for team collaboration.
According to the U.S. Bureau of Labor Statistics (BLS) for 2025, 8,290 people were employed in this occupation. The median pay was $69,460 per year, the lowest tenth earned $39,260, and the top tenth earned $130,860.
Use those numbers to set expectations: entry roles often sit toward the lower end, while specialized analysts who run surveys, write proposals, and manage teams can reach the higher end.
Use AI for routine tasks: drafting survey questions, summarizing results, or generating chart captions. Always check AI output against your raw data in Excel or SPSS — AI can hallucinate numbers or misstate sampling details.
Never let AI handle confidential data without anonymizing it first. Follow ethical standards: remove names/IDs, document any AI edits, and keep the original dataset and analysis steps in case you must explain decisions.
A Data Reporting Analyst focuses on collecting surveys, cleaning data, running standard analyses (often in SPSS), and producing reports and presentations. The role centers on survey methods, sampling, calibrating instruments, and communicating findings.
A Data Scientist usually builds predictive models, uses programming (Python/R), and works with large, varied datasets. If the job lists tasks like hiring recruiters, testing survey questions, and making PowerPoint summaries, it’s firmly in the reporting/ survey-analysis camp.
Take introductory statistics, survey methods, and courses in Excel (pivot tables and charts). A basic course in SPSS or another survey tool will help you run common tests and weight samples.
Also learn report writing (Microsoft Word), presentation skills (PowerPoint), and teamwork tools like Microsoft Teams. If you’ll work in the field, basic instrument handling and calibration are useful — many community colleges offer short courses.
Practical data cleaning and survey design understanding matter most. That means spotting sampling issues, handling nonresponse, and making data reliable in Excel or SPSS.
You also need clear communication: summarizing findings visually in PowerPoint and writing concise proposals or reports in Word. These skills let you convert messy survey data into decisions other people can act on.