# [Full Name]: ATS-Friendly Resume

> Resume template built to parse cleanly in applicant tracking systems
> (ATS) such as Workday, Greenhouse, Lever and iCIMS: one column, plain
> standard headings, no tables or graphics in the resume body, and
> wording aligned with the job description. Based on common recruiting
> and ATS practice. The keyword alignment table and formatting rules are
> working notes: delete them before you export the resume.

<!--
Guidance: How to use this template
- The resume body (sections 1 to 7) deliberately uses only headings,
  plain paragraphs and simple bullet lists. Do not add tables, columns,
  icons or text boxes to it; many parsers read them out of order or drop
  them.
- Fill section 9 (keyword alignment) first, using the job posting. Then
  write the resume so that every true match appears in plain words.
- Never hide keywords (white text, tiny font). Recruiters see the parsed
  text and it reads as dishonest.
- Export to .docx or a text-based PDF as the posting requests, then
  test it (section 10).
-->

| Field | Value |
|---|---|
| Target job title | [Data Analyst] |
| Company and requisition ID | [Company name, REQ-2026-0412] |
| Source of posting | [Company careers page / job board URL] |
| Export format | [.docx / PDF (text-based)] |
| Last updated | YYYY-MM-DD |

## 1. Contact information

<!-- Guidance: Put contact details in the body, not in the document header or footer; some parsers skip headers and footers. Use plain text, one item per line or separated by a vertical bar. -->

[Full Name]
[City, State or Region, Country]
[email@example.com] | [+00 000 000 000]
[linkedin.com/in/username] | [portfolio or GitHub URL]

## 2. Professional summary

<!-- Guidance: Three lines. Use the exact job title from the posting if it truthfully describes you, years of experience, two or three core skills from the posting, and one quantified result. -->

[Job title] with [N] years of experience in [domain]. Skilled in
[keyword 1], [keyword 2] and [keyword 3]. [One result with a number.]

*Example:* Data Analyst with 5 years of experience in e-commerce and
retail analytics. Skilled in SQL, Python, Tableau and A/B testing.
Built a demand forecast that cut stock-outs by 18% across 240 stores.

## 3. Skills

<!-- Guidance: A plain comma-separated or bulleted list. Spell out acronyms once alongside the short form ("Search Engine Optimization (SEO)") because postings and parsers use either. Group with simple labels if helpful, still in plain text. -->

- Technical: [SQL, Python (pandas), R, Excel (Power Query), dbt]
- Tools: [Tableau, Power BI, Looker, Google Analytics 4, Jira]
- Methods: [A/B testing, regression analysis, cohort analysis, forecasting]
- Business: [stakeholder management, requirements gathering, KPI design]

## 4. Work experience

<!-- Guidance: Standard order on one line: Job title, Company, Location, Dates. Use the same date format everywhere (MM/YYYY or Month YYYY). Three to six bullets per recent role, each starting with a verb and containing a skill keyword and a measurable result. -->

[Job Title]
[Company Name], [City, Country]
[MM/YYYY] to [Present]

- [Action verb] [task using keyword] resulting in [number].
- [Action verb] [task using keyword] resulting in [number].
- [Action verb] [task using keyword] resulting in [number].

*Example:*

Data Analyst
Harbor Retail Group, Manchester, UK
04/2022 to Present

- Built weekly sales dashboards in Tableau for 35 category managers,
  replacing 12 manual Excel reports and saving 20 hours per week.
- Wrote SQL models in dbt on Snowflake for promotions data, reducing
  report refresh time from 6 hours to 40 minutes.
- Designed and analysed 14 A/B tests on checkout pages; two winning
  variants raised conversion by 3.2% (about GBP 1.1 million per year).
- Developed a Python demand forecast (gradient boosting) that cut
  stock-outs by 18% across 240 stores.

Junior Data Analyst
Northgate Insurance, Leeds, UK
09/2020 to 03/2022

- Automated monthly claims reporting with Python and Power BI,
  reducing errors flagged by finance from 9 to 1 per quarter.
- Gathered requirements from 6 business teams and defined 22 KPIs in
  a shared data dictionary.

## 5. Education

<!-- Guidance: Degree, Major, Institution, Location, Year. Write the degree name in full and abbreviated form. -->

[Bachelor of Science (BSc), Major]
[University Name], [City, Country]
[YYYY]

*Example:* Bachelor of Science (BSc), Economics and Statistics,
University of Sheffield, Sheffield, UK, 2020

## 6. Certifications

<!-- Guidance: Official name of the certification, issuer and year, exactly as the issuer writes it, so it matches keyword searches. -->

- [Certification name], [Issuer], [YYYY]
- *Example:* Microsoft Certified: Power BI Data Analyst Associate, Microsoft, 2024
- *Example:* Google Data Analytics Professional Certificate, Google, 2021

## 7. Additional information

- Languages: [English (fluent), Polish (native)]
- Work authorisation: [Right to work in the UK] (include only if the
  posting asks)

## 8. Formatting rules (delete before export)

<!-- Guidance: These rules reflect how common parsers behave. Follow them for the body above. -->

1. **Single column.** No side bars, columns or text boxes. Parsers read
   left to right, top to bottom, and may merge columns into nonsense.
2. **Standard headings.** Use "Summary", "Skills", "Work Experience",
   "Education", "Certifications". Creative headings ("Where I have
   made an impact") may not be mapped to the right field.
3. **No tables, images, icons, charts or skill bars** in the resume
   body. Logos and photos are ignored at best.
4. **Common fonts** (Arial, Calibri, Helvetica, Georgia) at 10 to 12
   points; headings 12 to 14 points. Avoid ligature-heavy display fonts.
5. **Simple bullets** (round or hyphen). Avoid arrows and special
   symbols that can turn into question marks.
6. **Contact details in the body**, not in a header or footer.
7. **Consistent dates** in one format, with both month and year.
8. **File name** `Firstname-Lastname-Resume-JobTitle.docx` or `.pdf`.
   Export PDFs from a word processor, never as a scanned image.
9. **Length**: one page up to about seven years of experience, two
   pages beyond that.
10. **Spell-check** and use the posting's spelling of tools
    (PostgreSQL, not "Postgre"; JavaScript, not "Java Script").

## 9. Keyword alignment with the job description (delete before export)

<!-- Guidance: Copy the requirements from the posting into the first column, one per row, in the posting's wording. Mark whether you genuinely have the skill, and where it appears in your resume. Fill gaps only with true experience; if a "must have" is missing, address it in the cover letter or reconsider applying. Aim to cover at least 80% of the must-have keywords. -->

| Keyword or phrase (from posting) | Must / Nice | I have it? | Evidence (role, project, course) | Where in resume |
|---|---|---|---|---|
| [Keyword] | [Must] | [Yes / Partly / No] | [Evidence] | [Summary / Skills / Role 1 bullet 2] |
| *Example:* SQL | Must | Yes | Daily use at Harbor Retail, dbt models | Summary, Skills, Role 1 bullet 2 |
| *Example:* Tableau | Must | Yes | 35 dashboards built | Skills, Role 1 bullet 1 |
| *Example:* A/B testing | Must | Yes | 14 checkout tests | Skills, Role 1 bullet 3 |
| *Example:* Stakeholder management | Must | Yes | Requirements with 6 teams | Skills, Role 2 bullet 2 |
| *Example:* Looker | Nice | Partly | Online course, personal project | Skills |
| *Example:* Airflow | Nice | No | None | Not included |

Coverage: [N] of [M] must-have keywords matched ([percentage]).

## 10. Pre-submission test (delete before export)

<!-- Guidance: A five-minute test catches most parsing problems. -->

- [ ] Copy all text from the exported file into a plain-text editor.
  Everything appears in the right order and nothing is missing.
- [ ] Upload to the employer's form and check that the auto-filled
  fields (name, email, job titles, dates) are correct.
- [ ] Job title in the summary matches the posting wording.
- [ ] Every must-have keyword you possess appears at least once.
- [ ] No tables, images, columns, headers or footers in the body.
- [ ] A human reading it in 30 seconds understands your level, domain
  and best result.

## Standard and licence note

Based on common recruiting and applicant tracking system practice for
resume formatting and keyword alignment. Parser behaviour varies by
vendor and version; test with the employer's own form. Original text
written for this collection; example names and figures are fictional.
Template licence: MIT.