Resume Review · Sample

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Resume Review Report

A healthcare technology company Data Analyst

Aug 20, 2026, 10:15 AM

Feedback is generated from your input, and AI may make mistakes.

Slightly below

This resume is adequate, but several areas need more detail or improvement.

Two pages, twelve bullet points, and one number. A reader learns which tools you have touched and almost nothing about what happened afterwards.

Overall Feedback

The experience here is real and reasonably well matched to the role — SQL every day, a dashboard people actually use, a forecasting model in production. The resume just does not say so. Eleven of your twelve bullets describe what you were responsible for, and one describes what changed. A hiring manager spends six to eight seconds on the first pass; in that window, responsibilities all look the same and results do not.

Recommended Actions

Rewrite every bullet to end in a consequenceTake each line and finish the sentence "…which meant that…". If you cannot finish it, the bullet is a duty, not an achievement, and it should be cut or merged.
Replace the summary with three factsYears of experience, the domain, and the one result you would most want remembered. Four lines of adjectives is the most expensive real estate on the page.
Add scale to at least three bulletsNumber of users, rows, dollars, or decisions. Scale is what separates a senior analyst from a junior one on paper, and you currently give the reader nothing to judge it by.

Key Points

Strengths

The tooling matches the posting almost exactly

SQL, dbt, Python, and a BI tool are all named, and all four appear in the job description. You will pass a keyword screen without changing a word.

One bullet already does it right

The churn model line names the metric, the baseline, and the outcome. It is the only bullet a reader will remember, and it proves you can write the other eleven the same way.

The progression reads clearly

Analyst to senior analyst inside the same company, with widening scope. Nothing here needs explaining in an interview.

Needs Improvement

Eleven of twelve bullets stop at the responsibility

"Built and maintained dashboards", "supported the marketing team", "responsible for weekly reporting" — each is true, none is distinguishing. Every other applicant for this role did the same things.

The summary paragraph says nothing

"Detail-oriented data analyst with a passion for turning data into insights" appears on a large fraction of analyst resumes. It costs you the most valuable four lines on the page.

Scale is invisible

Nothing tells the reader whether the dashboards had five users or five hundred, or whether the pipelines moved thousands of rows or billions. Without scale, seniority has to be guessed from the job title.

Skills Radar

Technical depth8Tooling is current, and the dbt and modelling work is beyond entry level.
Impact evidence3.5One quantified outcome across twelve bullets.
Business framing5Work is described in analyst vocabulary rather than in terms of the decisions it supported.
Scope & scale4No user counts, data volumes, or dollar figures anywhere on the page.
Readability6.5Clean layout and consistent formatting; the summary and the length work against it.

Fit

SQL and data modelling8.5

Named in three roles with specific tooling (dbt, warehouse work). This is the strongest part of the application.

Turning analysis into decisions4

The posting leads with this. The resume shows analysis being produced, almost never being acted on.

Stakeholder communication5

"Supported the marketing team" and "presented findings" appear, but with no indication of what the audience did next.

Experimentation6

A/B testing is mentioned once in passing. For a healthcare product this is likely to be probed in interview.

Keyword Match (ATS)

71 / 100

Nine of thirteen terms from the posting appear on the page, and the technical ones are all there. What is missing clusters around the outcome side of the role — the words a hiring manager scans for when deciding whether you have done the job or only the tasks.

Matched

SQLPythondbtdata warehousedashboardETLA/B testingstakeholderreporting

Missing

data governanceHIPAAcohort analysisforecasting

Line-by-Line Rewrite Suggestions

Built and maintained dashboards for various internal teams.

Rebuilt the marketing team’s reporting in Looker, cutting the weekly manual pull from four hours to zero and taking the dashboard from 6 to 40 weekly users.

"Various internal teams" tells the reader nothing about scope. Hours saved and users gained are both checkable, and together they show the work was adopted rather than merely delivered.

Responsible for weekly and monthly reporting to leadership.

Owned the weekly executive metrics review; replaced a 30-slide deck with a one-page scorecard after tracking which slides were referenced in the meeting.

"Responsible for" describes a calendar, not a contribution. The rewrite shows judgement — you measured what was actually used, then cut the rest.

Supported the marketing team with ad hoc analysis.

Ran the analysis that ended a $180k/yr paid channel: attribution showed 70% of its conversions were already arriving through organic search.

"Supported" and "ad hoc" both minimise you. Naming the decision the analysis produced — and the dollar figure attached to it — is the single highest-value change on the page.

Detail-oriented data analyst with a passion for turning data into insights.

Data analyst, 3 years in subscription products. Built the churn model currently used to prioritise retention outreach; comfortable owning a question end to end, from warehouse to the meeting where it gets decided.

The original is on a large fraction of analyst resumes, which makes it worse than blank space. The rewrite gives the reader three facts and a claim they can test in the interview.

Tone & Verb Strength

The verbs cluster at the low-agency end. "Responsible for" appears five times, "supported" and "assisted" three times between them, and "helped" twice. Hiring managers read verbs as a proxy for how much of the work was yours, and this set reads as a contributor rather than an owner — which is at odds with a senior title.

passiveduty-focusedunderstatedcontributor voice

Suggested replacement verbs

Responsible for weekly reporting

Owned the weekly executive metrics review

Supported the marketing team

Partnered with marketing to

Assisted with data quality checks

Built the data quality checks that

Helped migrate legacy reports

Led the migration of 40 legacy reports

Formatting & Readability

62 / 100

Typographically clean — consistent dates, sensible headings, one font. The problems are structural: two pages for three years of experience, a four-line summary that carries no information, and a skills section that lists eighteen items without distinguishing between daily tools and things you touched once.

Two pages for three years

At this level a reader expects one page and will assume the second is padding. Cutting the coursework block and the two pre-graduation internships gets you there without losing anything a hiring manager wants.

The summary occupies the best four lines and says nothing

Everything above the first job is prime real estate. "Detail-oriented" and "passion for data" are claims every applicant makes, so they cost you the position without buying attention.

Skills listed flat, eighteen items, no grouping

SQL sits between Microsoft Excel and Jira. The reader cannot tell what you use daily from what you have opened once, so they discount the whole list.

Bullet length is uneven

Some bullets run three lines, others four words. The long ones bury their point at the end and the short ones look like filler.

Mock Interviewer Perspectives

Hiring manager61

Looks for judgement

Reads the bullets looking for a decision that changed because of the analysis, finds one, and has to decide whether that is a writing problem or a work problem. Will probably interview, and will open with "walk me through the churn model".

Tooling is exactly right for the team

The churn model bullet shows real ownership

Cannot tell what any of the other work led to

No sense of scale anywhere

Recruiter screen70

Six seconds

Scans for the stack, finds it, passes it on. The two-page length costs nothing at this stage and the summary is skipped entirely. This is the easiest gate in the process for this resume.

All required tools present and easy to find

Clean formatting, no parsing risk

Nothing distinguishing if the pile is large

Analyst on the team66

Will you make my life easier

Notices dbt and the legacy report migration, which suggests someone who cleans up rather than adds to the mess. Would want to know how the churn model is maintained now — a model in production with no owner named is a small red flag.

dbt experience is uncommon at this level

Migrated legacy reports rather than leaving them

No mention of testing or documentation

Unclear who owns the model now

Questions you may be asked

Walk me through the churn model — how was it built, and is it still being used?

Why they'd ask: It is the only quantified bullet on the resume, so it will carry the weight of the whole application. Expect it first.

How to answer: Have the baseline, the features that mattered, and the current state ready. If it is no longer in use, say so and say why — a model that was retired for a good reason is a better story than a vague claim that it still runs.

Tell me about an analysis where the answer was not what the stakeholder wanted.

Why they'd ask: The posting leads with translating analysis into decisions, and nothing on the resume shows an analysis meeting resistance.

How to answer: The paid-channel finding is the story. Include what the channel owner said and what you did with the objection, not just the conclusion.

What is your process for making sure a number you publish is right?

Why they'd ask: Healthcare data raises the cost of being wrong, and the resume mentions data quality checks only as something you assisted with.

How to answer: Describe an actual check you built and one time it caught something. Generic answers about "validating against source systems" will not distinguish you.

Other roles worth considering

Analytics Engineer8

The dbt work and the legacy migration point this way, and the field values exactly the thing your resume currently shows best — building things other people rely on.

Product Analyst7

The churn model and the A/B testing mention fit, and the role rewards the decision-framing you would need to develop anyway.

Business Intelligence Developer6.5

A safe adjacent target if the analyst pipeline is crowded, though it leans further from the decision-making side of the posting you are aiming at.

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