Compensation landscape
Describe distributions and outliers by role, experience, company size, geography, and work arrangement without treating record counts as market demand.
36-613 · final report
Global Data & AI Workforce Compensation Analytics
Advise an executive-search steering committee on where to build a data-and-AI recruiting practice, which talent lanes to prioritize, and how compensation evidence should shape the pitch.
Due Friday, October 9 at 11:59 p.m. Eastern. Submit one self-contained HTML file through the Gradescope assignment linked from Canvas. Rubric boundary: The 36-613 Data Vis Rubric grades this report; the Professional Skills Rubric is a separate working draft and is not the Data Visualization grading rubric. Evidence boundary: the archive is useful for directional compensation comparisons, not for measuring employer demand or the full labor market.
Client assignment
Turn salary records into a recruiting decision
Your team is the analytics group for an executive-search firm. Select a defensible target employer, identify the roles and experience tiers worth building a pipeline around, and show the steering committee what to approve, pilot, reject, or investigate next.
Career and market signals
Evaluate salary differences over time and across career tiers. Distinguish descriptive evidence from causal claims and flag thin or changing samples.
Recruiting playbook
Recommend a target employer and priority talent lanes, with compensation benchmarks, tradeoffs, and an explicit list of claims the archive cannot support.
Submission
One self-contained HTML report
Due Friday, October 9 at 11:59 p.m. Eastern. Open the Gradescope assignment from Canvas and submit one HTML file. The companion-course presentation is not part of the Data Visualization grade.
Single-file submission
Produce the report from Quarto/R Markdown with embed-resources: true, so figures, styling, and other assets travel inside the HTML. Do not submit a ZIP, separate folder, or source file.
Embedded reproducibility
Include data-source links, cleaning and duplicate-handling decisions, relevant code, role-grouping rules, package information, and limitations inside the report.
Required evidence
Questions the report must resolve
01Audit
What can this archive actually tell us?
- Explain what one supplied row represents and what cannot be verified.
- Audit exact duplicates, year coverage, geography, company size, and remote-status fields.
- State how the audit changes the claims you are willing to make.
02Analyze
Where are the meaningful compensation differences?
- Compare relevant roles and experience tiers.
- Examine time, geography, company size, and remote work only where sample support is credible.
- Use transformations, uncertainty, or modeling when they improve the visual argument.
03Decide
What should the search firm do?
- Choose and justify a target employer using appropriate external evidence.
- Prioritize roles, levels, and recruiting lanes with directional pay benchmarks.
- End with what to approve, pilot, reject, and commission next.
Minimum standards
Report requirements
- Six to ten visualizations forming one cohesive client story.
- At least three client questions and no more than three plots of the same type.
- A mix of foundational and later-course forms; no more than two one-variable plots.
- At least one statistical analysis, model summary, sensitivity analysis, or uncertainty display that complements a graph.
- Clear units, subsets, denominators, nominal-dollar status, sources, and sample sizes where they matter.
- A conclusion with recommendation, tradeoffs, data gaps, and a practical next evidence request.