Research Assistant
@ Crossing Hurdles

Hybrid
$60,000
Hybrid
Contractor
Posted 23 days ago

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XXXXXXXXXX XXXXXXXXXXX XXXXXXXXX******* @crossinghurdles.com
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Job Details

Overview

Crossing Hurdles is a recruitment firm referring top candidates, including recent graduates and entry-level professionals, to world-leading AI research labs. The Research Assistant role involves working as Editors, Fact Checkers, and Data Quality Reviewers on an hourly contract basis.

Role Responsibilities

  • Create and design research-style prompts with browsing and validation.
  • Review model-generated responses for accuracy, completeness, and clarity.
  • Cross-check facts, spot inconsistencies, and validate multiple sources.
  • Provide clear, structured feedback to improve data quality and model reliability.
  • Collaborate remotely with AI researchers and other reviewers.

Requirements

Bachelor’s degree or current graduate status; recent graduates or students with strong critical thinking and writing skills are welcome. Must be detail-oriented, analytical, and proficient in fact verification and research. Ability to work independently and manage time effectively is essential.

Application Process

  • Submit a short application form with relevant skills and background.
  • Complete a brief video or phone interview (20–30 minutes).
  • Participate in a short screening or skills test.
  • Receive onboarding instructions and project access within 1–2 days upon approval.

Key skills/competency

  • Research
  • Fact-checking
  • Editing
  • Data Quality
  • Analytical
  • Critical Thinking
  • Communication
  • Detail-Oriented
  • Remote Collaboration
  • Time Management
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How to Get Hired at Crossing Hurdles

🎯 Tips for Getting Hired

  • Customize your resume: Align skills with research and data quality.
  • Highlight relevant experience: Emphasize research and editorial abilities.
  • Prepare for interviews: Practice fact-checking and analytical questions.
  • Showcase communication skills: Share clear and concise examples.

📝 Interview Preparation Advice

Technical Preparation

Review research methodologies and data validation techniques.
Practice using online fact-checking tools.
Familiarize with AI model outputs and quality metrics.
Brush up on structured feedback writing.

Behavioral Questions

Describe a time you solved data inconsistencies.
Explain working independently in a remote setting.
Discuss handling feedback under tight guidelines.
Share examples of managing multiple tasks.

Frequently Asked Questions