Data Analyst | Problem-Solving Resume

Prompt

Create an editable two-page A4 resume for a fictional data analyst: use three case studies, on metric definitions, retention segmentation and operational experiments, to show the problem, method, deliverable and impact still to be validated; include SQL, Python and visualization skills and a one-page metric definition case. Use dark blue, light gray and orange, and label all people and data "Sample content". Write all content, headings, labels, sheet names and file names in English.

Result

docx
Data Analyst | Problem-Solving Resume

PROFILE

Data analyst with six years of experience turning ambiguous business questions into measurable, well-documented metrics. Builds SQL and Python pipelines that keep definitions consistent across teams, designs retention segments that survive scrutiny, and runs operational experime…

CORE SKILLS

CASE STUDY 01 METRIC DEFINITION CASESample content

One page: standardizing “active user” and a north-star metric set across three product teams

PROBLEM Three product teams reported weekly active users from the same warehouse and disagreed by up to 18% (sample data). Roadmap and staffing decisions used incompatible numbers; no one owned a definition, and near-identical SQL had been copied into a dozen dashboards.

METHOD Inventoried 40+ metric references across dashboards, documents and queries. Interviewed product, finance and support stakeholders to map each team’s real decision. Drafted a decision-rights table (owner, approver, reviewer), then wrote canonical definitions as versioned d…

DELIVERABLE A metric dictionary with the specification below, 14 dbt data tests, a definition-change review checklist, and a one-page executive summary that states what changed and what did not.

IMPACT — TO BE VALIDATED Expected: one agreed WAU definition adopted by all three teams, removing the ~18% reporting variance at source. Validation plan: re-run the reconciliation weekly for four weeks and compare team-reported against canonical WAU, with a target of ≤2% varianc…

CASE STUDY 02 RETENTION SEGMENTATIONSample content

Alex Morgan — Data Analyst, a fictional two-page A4 resume, delivered as an editable Word document (not a PDF) so you can rewrite, re-brand and re-print it.

Verified: exactly 2 A4 pages (210 × 297 mm) with 11 / 10 / 13 / 13 mm margins, measured with a real DOCX layout engine and checked page by page; page 1 fills to within 20 mm of the bottom margin, page 2 to within 18 mm; no text clipping, no table crossing the side margins.

Page 1 — navy header band with name, role and a "Sample content" marker; light-gray contact strip; profile; a three-column skill matrix covering SQL (CTEs, window functions, dbt, data-quality tests), Python (pandas, scikit-learn, Airflow) and visualization (Tableau, Power BI, Looker Studio, Matplotlib); then Case Study 01 — Metric Definition, the one-page case, with problem, method, deliverable, a five-metric specification table (WAU, qualifying action, activation rate, report freshness, definition drift) and an impact marked "to be validated".

Page 2 — Case Study 02 — Retention Segmentation and Case Study 03 — Operational Experiments, each structured Problem → Method → Deliverable (three bullets) → Impact, to be validated → Validation plan; a deliverable index table (artifact, type, audience, status); education and tools; footer disclaimer.

Every person, organization and figure is labelled sample content — in the header, on each case-study bar, in the education block and in the page footer — and no impact is claimed as achieved: each one names the hypothesis, the measurement and the guardrail instead.

Two notes on your brief: the document contains no sheets, since it is a Word file rather than a workbook, so there were no sheet names to set; and all text, headings, labels and the file name are in English, using US spelling throughout. Everything is real Word content — styles, paragraphs and tables rather than images — so text, colours and page setup stay editable.

How it was made

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