AI Data Quality Analyst

About Eqvista

Eqvista is an integrated SaaS system that helps companies to manage private company equity by minimizing costs by automation, accounting, sharing and compliance tools built into the system. We also provide an array of valuation services for helping founders find their valuation for fundraising and ESOP issuance (409a)

Please visit: https://eqvista.com/ to learn more about our company.

For more open position, please visit: https://eqvista.com/careers/

We are seeking a detail-oriented AI Data Quality Analyst to ensure the accuracy and integrity of data used and produced by our AI systems. This role involves validating various types of documents and datasets by cross-checking them against AI outputs to maintain reliable, trustworthy, and high-quality data for AI model training and decision-making purposes.

Key Responsibilities:

• Verify and validate data from diverse document types against AI system outputs for accuracy and consistency.
• Perform detailed data audits and check for discrepancies or mismatches between source data and AI results.
  
• Collaborate with AI model developers, data specialists and research analysts to address and resolve data quality issues.
• Maintain documentation of data validation processes, anomalies detected, and corrective actions taken.
• Use data quality and validation tools to streamline and automate validation workflows.
• Ensure compliance with internal data standards and regulatory requirements where applicable.
• Support continuous improvement initiatives for data validation techniques and AI model data inputs.

Requirements:

• Bachelors degree in Computer Science, Information Technology, Data Science, or related field.
• Two years experience in data validation, quality assurance, or a related analytical role, preferably involving AI systems.

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• Strong attention to detail with excellent analytical and problem-solving skills.
• Familiarity with data validation tools, databases, and data wrangling techniques (e.g., SQL, Python, Pandas).
• Ability to work independently and in collaboration with cross-functional teams.
• Good communication skills to report findings and coordinate with team members.

Preferred Skills:

• Understanding of AI/ML model data requirements.
• Knowledge of document verification processes and tools.
• Experience using cloud platforms (AWS, Azure, Google Cloud) and data observability tools.