Your work. Your records.
Data Scientist Workplace Records
Data scientists may define an analysis, prepare data and test models before presenting findings to decision-makers. A workplace concern often depends on which objective or evaluation standard was in effect. Describe your contribution and the available information at the time, then connect the technical instruction to the employment decision without exporting the project’s data or code.
Call now(800) 800-5555Free initial case evaluation. Representation depends on work state and case eligibility. This guide explains record preparation; it does not determine whether a legal claim exists.
A record map for your role
What to organize first
Requirement history
List the original objective, evaluation metric and approved changes, with the date each became known to you.
Review sequence
Identify validation concerns, your recommendation and the approval or response, separating your actions from decisions made by product or management teams.
Employment chronology
Connect the technical instruction with your own feedback or reassignment while leaving datasets, model artifacts and code in their approved systems.
Start with the work you actually do
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.
O*NET classifies this occupation as Data Scientists (15-2051.00). Its description covers a typical occupation, not every workplace or individual job. It does not establish employee status, overtime eligibility or employer misconduct.
- Analyze, manipulate, or process large sets of data using statistical software.Source task 21823 · updated 08/2026
- Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.Source task 21828 · updated 08/2026
- Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.Source task 21837 · updated 08/2026
- Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.Source task 21829 · updated 08/2026
A reference point for your pay records
May 2025 wage estimates by state
Compare your pay records with published BLS estimates for Data Scientists (SOC 15-2051). These describe an occupation across employers. They are not a required pay rate, an overtime calculation, or evidence of discrimination or unpaid wages.
Select your work state to see its published pay range. No personal pay information is requested or sent.
The 25th and 75th percentiles mark the middle half of the estimated wage distribution; the median is its midpoint. Actual pay can differ with experience, employer, location and duties. Hourly and annual figures are shown as published, without converting one into the other.
All published state estimates for this occupation
| State | Hourly 25th | Hourly median | Hourly 75th | Annual median |
|---|---|---|---|---|
| Alabama | $35.64 | $49.58 | $61.38 | $103,120 |
| Alaska | $27.57 | $40.44 | $54.34 | $84,110 |
| Arizona | $38.85 | $51.56 | $64.46 | $107,240 |
| Arkansas | $46.88 | $52.59 | $65.41 | $109,390 |
| Connecticut | $45.42 | $60.74 | $78.47 | $126,340 |
| Delaware | Not published | Not published | Not published | Not published |
| Florida | $40.42 | $55.69 | $67.41 | $115,820 |
| Georgia | $40.44 | $50.16 | $65.66 | $104,340 |
| Hawaii | $42.13 | $49.10 | $73.55 | $102,130 |
| Idaho | $38.91 | $42.97 | $65.84 | $89,380 |
| Indiana | $34.94 | $43.98 | $61.30 | $91,470 |
| Iowa | $34.14 | $46.07 | $61.22 | $95,830 |
| Kansas | $36.52 | $47.18 | $63.17 | $98,130 |
| Kentucky | $36.35 | $44.12 | $58.58 | $91,760 |
| Louisiana | $30.56 | $37.86 | $52.95 | $78,760 |
| Maine | $37.18 | $43.69 | $55.37 | $90,880 |
| Michigan | $37.22 | $48.36 | $62.62 | $100,590 |
| Minnesota | $44.46 | $61.92 | $77.36 | $128,800 |
| Mississippi | $24.55 | $33.41 | $47.61 | $69,490 |
| Missouri | $35.87 | $46.68 | $61.39 | $97,090 |
| Montana | $34.13 | $48.31 | $61.46 | $100,490 |
| Nebraska | $38.90 | $47.23 | $52.82 | $98,230 |
| New Hampshire | $39.78 | $48.37 | $61.80 | $100,620 |
| New Mexico | $30.89 | $46.08 | $51.70 | $95,850 |
| New York | $45.62 | $62.72 | $82.49 | $130,460 |
| North Carolina | $39.63 | $57.25 | $70.93 | $119,090 |
| North Dakota | $30.90 | $39.37 | $48.13 | $81,900 |
| Ohio | $38.23 | $49.34 | $62.94 | $102,630 |
| Oklahoma | $32.97 | $41.49 | $52.78 | $86,310 |
| Pennsylvania | $38.09 | $51.37 | $62.09 | $106,850 |
| Rhode Island | $44.76 | $49.25 | $62.57 | $102,440 |
| South Dakota | $40.29 | $46.22 | $59.26 | $96,150 |
| Tennessee | $37.39 | $48.24 | $63.43 | $100,330 |
| Texas | $40.33 | $58.70 | $70.21 | $122,090 |
| Utah | $37.85 | $51.97 | $70.27 | $108,090 |
| Vermont | $47.33 | $61.09 | $68.83 | $127,070 |
| Virginia | $46.82 | $60.79 | $79.62 | $126,430 |
| West Virginia | $33.55 | $40.91 | $54.21 | $85,090 |
| Wisconsin | $42.34 | $51.29 | $64.36 | $106,680 |
“Not published” preserves unavailable or suppressed source cells. “Above reporting limit” preserves a top-coded source value without inventing a number. A missing state estimate does not establish service eligibility. The data describe wage and salary employment; they do not measure self-employment income.
Source: BLS May 2025 state workbook · OEWS tables · BLS technical notes. Use your own schedule, pay statement and compensation terms to identify the question you want reviewed.
Identify the objective and evaluation version
Record the question the model was intended to address, the agreed metric and the version of the evaluation procedure relevant to the dispute. Note changed labels, data availability or revised success criteria that you reported. Separate an experimental result from an approved deployment decision. A later metric does not necessarily show what standard guided your original assignment.
Trace validation and recommendation decisions
Describe the checks you performed, limitations you raised and the person who decided whether to use the result. If a concern involves pressure to change a conclusion, record the instruction and your response without copying confidential analysis. Distinguish an unresolved technical question from a confirmed defect. Keep permitted assignment and evaluation messages to show who controlled the next step.
Protect datasets and analytical assets
Do not export raw datasets, personal identifiers, model artifacts, proprietary code or access credentials into a personal employment archive. Identify a relevant experiment or report by type and stored location instead. Use your own employment terms, review and dated notes to explain the workplace issue. Do not access a repository after permission ends or recreate sensitive data merely to support your account.
Choose your next step
Review the workplace retaliation guide, unpaid wages guide, or discrimination guide if those concerns fit your experience. A job title alone does not establish a claim.
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