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Remote
40 Open Positions
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500 Employees or more · Scientific Research & Development

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Job description

Job Title: Data Analyst


Job Type: Contractor


Location: Remote


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Conduct in-depth data analysis using Microsoft Excel to extract actionable insights and support decision-making across teams.
  2. Collaborate with project stakeholders to understand data requirements and translate them into meaningful analyses.
  3. Review, clean, and validate datasets to ensure accuracy, consistency, and integrity.
  4. Develop clear, concise reports and visualizations to communicate findings to both technical and non-technical audiences.
  5. Identify trends, anomalies, and opportunities in complex datasets, contributing to strategic initiatives.
  6. Document methodologies, results, and recommendations with meticulous attention to detail.
  7. Contribute expertise to enhance data-driven decision-making processes within the customer's team.



Required Skills and Qualifications:

  1. Proven experience performing data analysis in a business environment using Microsoft Excel as the primary tool.
  2. Exceptional attention to detail and accuracy in data processing and reporting.
  3. Strong written and verbal communication skills, with the ability to clearly articulate analytical findings.
  4. Demonstrated ability to work collaboratively across teams to drive business outcomes.
  5. Solid understanding of Excel functions, formulas, and data visualization tools.
  6. Proficiency in identifying data inconsistencies and implementing corrective measures.
  7. Experience working in fast-paced, data-driven organizations.



Preferred Qualifications:

  1. Experience supporting cross-functional teams with data insights to inform business strategy.
  2. Background in presenting analytical outcomes to diverse audiences.
  3. Familiarity with additional data analysis tools or business intelligence platforms.
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