Reverse Recruiting Agency

Resume Writer Challenge

Short skills test: Original Bullet → AI Bullet → Final Suggested Bullet

Estimated time: 10–15 minutes Best on desktop

About You

Paste your LinkedIn profile URL

Maximum 2 files. Accepted formats: PDF, DOCX.

Client Profile: “A.S.”

Current Status

Actively searching

Experience Level

15+ years in BI, marketing analytics & revenue operations

Education

MBA in Finance & Strategy (top business school); Master of Computer Applications

Target Roles

Analytics Manager, Senior Data Analyst, Data Analytics Manager

Target Industries

Marketing Analytics, Financial Services

Target Salary

$125,000 – $175,000

Location

Remote only, based in Seattle

Key Skills

Snowflake, Snowpark, SQL, Python, Tableau, SAS, Data Modeling, Google Analytics, A/B Testing, ETL Pipelines, Master Data Management

Difficulty Note: This client completed only 3 interviews from 314 applications, trailing peers who have up to 15 interviews in the same period. His resume bullets read like job descriptions rather than achievement stories. He needs bullets that clearly show intervention, ownership, and measurable impact.

The Challenge

Here's how our resume process works and what we need from you:

  1. 1
    We onboard the client. They sign up, and we collect their original resume, LinkedIn profile, intake form, call transcripts with the founder of RRA, and other contextual information about their background and goals.
  2. 2
    We review the client's original resume. Their bullet points are often vague, duty-focused, and missing quantified impact and achievements. You'll see these labeled ORIGINAL in amber.
  3. 3
    AI rewrites each bullet using our achievement framework. It adds structure (situation → action → outcome), inserts tools and stakeholders, proposes metrics, and most importantly, achievements. AI has all the context about the candidate. Bold text in the AI rewrite means the AI added or fabricated that detail. Labeled AI REWRITE.
  4. 4
    A human resume writer refines the AI output before we send it to the client. This is your job. Improve the AI rewrite: tighten the language, make it sound more natural, fix anything that feels robotic or over-engineered, and ensure the story is clear and compelling. Write your version in the YOUR REWRITE field.
Your goal: For each bullet, write a final version that is tighter, more natural, and more compelling than the AI output. You don't need to start from scratch — treat the AI rewrite as your starting point and make it better.
A note on context: We know this is an unusual exercise. In a real engagement, you'd have a full client intake, a conversation about their career story, and much more background to work with. Here, we're giving you limited information. We want to see how you think about bullet construction, what instincts you bring, and how you'd improve on what the AI produced, even without the full picture.
Job 1

“Company A” — Information Management Analyst, Marketing

January 2025 – Present  ·  Fortune 100 insurer & financial services company. Household name, millions of members nationwide.

Bullet 1

Original

“Designed Snowflake data structures for scalable data ingestion and analytics”

AI Rewrite

“Architected Snowflake data structures to support scalable ingestion across [3-5] marketing data sources, replacing a fragmented SQL-based pipeline that previously required [X hours] of manual reconciliation per week

Your Rewrite

Bullet 2

Original

“Built unified marketing dashboards integrating Google Analytics, GCM, and paid media”

AI Rewrite

“Built a unified marketing performance dashboard in Tableau integrating Google Analytics, GCM, and paid media datasets, giving the marketing team single-pane visibility into [$X M] in annual ad spend for the first time

Your Rewrite

Bullet 3

Original

“Created automated QA workflows for paid media data using third-party APIs”

AI Rewrite

“Automated QA workflows for paid media data by integrating third-party APIs (Google Ads, Meta, GCM) into Snowflake pipelines, reducing data validation time by [X%] and catching [X] discrepancies per month that previously went undetected

Your Rewrite
Job 2

“Company B” — Business Intelligence Analyst

January 2020 – December 2024

A small, local investment fund. The client knows the owner personally. Lean team, broad responsibilities.

Bullet 1

Original

“Modernized KPI reporting for real-time operational and revenue visibility”

AI Rewrite

“Redesigned KPI reporting infrastructure to deliver real-time operational and revenue dashboards, replacing batch-updated Excel reports that were [X days] stale; leadership used the new dashboards to make [pricing/staffing/inventory] decisions [X% faster]

Your Rewrite

Bullet 2

Original

“Built Tableau dashboards on SQL Server and Snowflake backends”

AI Rewrite

“Built [X+] Tableau dashboards on SQL Server and Snowflake backends serving [X] business users across operations, finance, and sales, standardizing previously siloed reporting into a single governed analytics layer

Your Rewrite

Bullet 3

Original

“Led master data management initiatives ensuring accuracy, timeliness, and completeness”

AI Rewrite

“Led a master data management program across [X] data domains, implementing validation rules and governance workflows that improved data accuracy from [X%] to [X%] and reduced downstream reporting errors by [X%]

Your Rewrite

Feedback & Comments

Any thoughts on this exercise, our process, or anything else you'd like to share? Completely optional.

All bullet rewrites and LinkedIn URL are required