r/BigDataJobs

What Recruiters Look for in a Resume and What Happens Before They Look
▲ 17 r/BigDataJobs+10 crossposts

What Recruiters Look for in a Resume and What Happens Before They Look

The most quoted resume statistic, about seven seconds per resume, comes from a 2018 Ladders eye-tracking test of 30 recruiters which measured an average of 7.4 seconds on the first review. It is a small sample, describing a step many resumes never reach.

The search comes first

Online applications usually land in an applicant tracking system. Recruiters search it by keyword, title and qualification, then read the results. Relevant experience described in words other than the posting’s is less likely to appear. Spelling an acronym out once, as in “Kubernetes (K8s)”, lets a search for either form find it.

Then the seven seconds

Once a resume is opened, the Ladders test found attention going mostly to a few fields: current title, most recent company, dates and education. A bullet with a percentage, amount or headcount tells a quick reader more than one that begins “Responsible for.”

A closer read asks other questions. Do the scope and seniority fit, not just the job family? Are the tools recent? Is the writing free of typos?

Order matters

Many applicants start with layout. Two-column designs, tables and text boxes can scramble text when the system extracts it. Standard headers, a single column and the posting’s own terms serve the search. Quantified results and a readable career line serve the person.

ZoeVera’s guide to what recruiters look for in a resume . To see which of a posting’s terms your resume lacks before you apply, ZoeVera Resume compares the two and lists the gaps.

u/Enough_Charge2845 — 5 days ago

[Hiring] [Remote] Experienced Data Scientists / Data Analysts Wanted for AI Training | Starting at $40+ USD/hr

There are remote roles available for individuals geographically located in the United States, Canada, United Kingdom, Ireland, Australia, and New Zealand.

The work involves evaluating AI-generated analyses using real datasets, checking the accuracy and validity of conclusions, and producing clear technical explanations and well-documented analytical code.

Requirements:

  • Strong professional background in data science, data analysis, statistics, or a closely related quantitative field
  • Experience working with real-world datasets and applying appropriate data analysis methodologies
  • Ability to evaluate analytical conclusions for accuracy and identify errors in reasoning or methodology
  • Comfortable writing clear technical explanations and well-documented analytical code
  • Experience with tools/languages such as Python, R, SQL, or similar data analysis technologies is preferred

Details:

  • Employment type: Independent contractor / freelance for Data Annotation Tech
  • Pay: $40+ USD/hr, depending on project and expertise
  • Schedule: Flexible and fully remote
  • Work may include evaluating AI-generated data analyses, reviewing statistical reasoning, working with datasets, and assessing the quality of analytical code and conclusions

Additional Details: An online assessment is required to be completed successfully prior to onboarding.

For more information, questions, or sign-up details, please send a DM with the following information:

Country:
Degree / Field:
Professional or research experience with data analysis/data science: How many years, and in what area?
Main tools: (Python / R / SQL / etc.)

Please leave the comment "DM Sent" after you've sent your message so I can prioritize your message and in case your DM didn't get through the first time. Thank you!

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u/WaldensPond — 11 days ago