Senior Data Analyst

Role overview

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.

Requirements & 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.

Skills

• Personal Identifiable Information
• Quality Assurance
• Attention to Detail
• Data Analysis
• Business Data Sets