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:

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

Required Skills and Qualifications:

1. Bachelor's degree in business, analytics, statistics, information systems, or a related field (or equivalent professional experience).
2. 3+ years of experience as a Business Analyst or Data Analyst working with large business data sets.
3. Hands-on experience with QA processes, such as data validation, reconciliation, and verifying analytical outputs.
4. Demonstrated expertise in handling and analyzing large business data sets.
5. Proven experience managing data containing personally identifiable information (PII) and sensitive material.

Preferred Qualifications:

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