Claude Prompts for Data Analyst Job Search

You are an expert recruiter for data analyst roles. Here is my resume:

[PASTE RESUME]

And the job description:

[PASTE JOB DESCRIPTION]

Rewrite my bullet points to match this role. Lead each with business impact (a decision made, money saved, time reduced, a metric moved), quantify it, and mirror the exact tools and terms from the job description (for example SQL, Python, Tableau, Power BI, dbt, A/B testing) without inventing anything. Flag any stretch.

Act as an ATS parser for data analyst roles. From this job description:

[PASTE JOB DESCRIPTION]

List the tools, languages, methods, and exact keyword phrases (for example SQL, ETL, cohort analysis, forecasting, stakeholder management) an ATS would score against, ranked by prominence. Then tell me which are missing from my resume:

[PASTE RESUME]

and where I could add each one truthfully.

Help me quantify this data analyst project for my resume: [DESCRIBE PROJECT]. Ask me up to 4 questions to surface the impact (who used the analysis, what decision it drove, what changed, how much time or money it affected). Then write 2 resume bullets in the format 'accomplished X by doing Y, resulting in Z'.

Write a concise cover letter for this data analyst role:

[PASTE JOB DESCRIPTION]

Using my background:

[PASTE RESUME OR SUMMARY]

Under 250 words, no cliches. Open with a concrete reason I fit this team or domain, cite one analysis I ran and the decision it drove, and close with a clear call to action. Match the company's tone.

Write a 4 to 5 sentence LinkedIn message to the hiring manager for this data analyst role: [PASTE ROLE AND COMPANY]. Introduce me briefly, give one specific reason I am interested in their team or product, and mention one relevant analysis I have done ([DETAIL]). Warm, human, under 90 words.

Act as a hiring manager interviewing me for a data analyst role. Give me one realistic analytics case question (for example: our sign-ups dropped 15% last month, how would you investigate; or how would you measure the success of a new feature). After I answer, probe like a real interviewer: clarify the metric, ask about data I would pull, confounders, and how I would present findings. Then tell me what a strong answer would include. Ask the question now and wait.

I need to practice explaining analysis to a non-technical stakeholder. Give me a scenario where I have to present a finding from [TOPIC, for example a churn analysis] to a [ROLE, for example VP of Marketing]. Play the stakeholder: ask the blunt, practical questions they would ask ('so what should I do?', 'how confident are you?'). After a few rounds, tell me where I was too technical or buried the recommendation.

Generate a warm-up set for a data analyst technical screen: 5 SQL questions rising in difficulty (joins, window functions, cohort or funnel logic) with a sample schema, plus 2 short take-home style prompts. Give me the questions first. After I attempt each, show the ideal solution and explain the reasoning, not just the answer.

Compare my resume against job descriptions for [TARGET ROLE, for example Senior Product Analyst]. My resume: [PASTE RESUME]. Target job descriptions: [PASTE 2 to 3]. Identify the specific tool, method, and domain gaps between me and these roles, ranked by how much they matter, and for each suggest the fastest credible way to close or reframe it.