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Role Title: Senior Data Analyst

Role Type: Contractor

Location: Remote, US Based only

Job Summary: We are seeking seasoned U.S.-based Senior Data Analysts for a part-time role at the forefront of AI. This opportunity is for accomplished data professionals who want to help shape how advanced AI is trained, evaluated, and applied to real-world data work. We are especially interested in analysts with deep experience working with large business data sets, strong quality assurance practices, and a meticulous eye for detail. Experience handling personally identifiable information (PII) is a plus.

Key Responsibilities:

• Review data sets for PII, flagging sensitive information and following data privacy best practices.
• Review and assess AI responses to data and business analysis scenarios, providing expert feedback to improve accuracy and precision.
• Apply QA practices to validate data quality, flag inconsistencies, and verify the correctness of analytical results.
• Create objective evaluation frameworks and grading criteria to assess AI performance on analytical tasks.
• Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven analytics.

Required Skills and Qualifications:

• Bachelor's degree in business, analytics, statistics, information systems, or a related field (or equivalent professional experience).
• 3+ years of experience as a Business Analyst or Data Analyst working with large business data sets.
• Hands-on experience with QA processes, such as data validation, reconciliation, and verifying analytical outputs.
• Demonstrated expertise in handling and analyzing large business data sets.
• Proven experience managing data containing personally identifiable information (PII) and sensitive material.

Preferred Qualifications:

• Familiarity or experience working with PII, including data privacy and handling best practices.
• Proficiency with SQL, Excel, and BI or visualization tools.
• Advanced degree or professional certification in business analysis or data analytics.
• Prior exposure to AI, data labeling, or model evaluation initiatives.