Own the data model understanding end-to-end; identify and recommend reporting remediation or schema changes when compliance processes shift Establish expertise across a system that's focused on reviewing and mitigating product risks Establish risk expertise across multiple areas including privacy and integrity Identify gaps in risk assessments and determinations made by product stakeholders Monitor KCIs to ensure system effectiveness and drive incremental improvement of associated controls Investigate KCI breaches, attest to results, and meet alert SLOs Supply KCI history for evidence packages when requested by regulators Ensure a complete and comprehensive representation of Meta's compliance framework to both internal and external stakeholders as needed Build and execute complex Presto/Hive population queries for regulator requests (population requests, sample requests, information requests, follow-ups) Respond to regulatory queries and partner with compliance partners and other stakeholders to develop and/or respond to gap analysis language, respond to regulator evidence requests by producing correct, reproducible artifacts with proof anyone can audit Create runnable Bento notebooks that reviewers can independently execute to verify results Create high quality action plan documentation to address compliance gaps where needed Explain and rationalize compliance and risk decisions to external stakeholders including auditors and regulators Track and provide any needed documentation that stems from remediation workflows Provide feedback to tooling and platform stakeholders aimed at improving the accuracy and efficiency of the system's outcomes Explain and defend data methodologies to regulators as needed4+ years of experience with regulatory/compliance/audit exposure in an analytical role Familiarity with SQL, scripting languages (e.g., Python), and AI for compliance Demonstrated analytical thinking and problem-solving experience Able to explain and create code and objects as needed (e.g., Python) for evidence and tooling Ability to work cross-functionally between engineering and various POC teams Detail-oriented, conscientious focus for data quality and privacy processes Experience communicating cross-functionally, particularly in the area of consensus-building and persuasion Ability to work with tight, inflexible regulator deadlines Flexibility to respond and change quickly to vague, uncertain, frequently changing requests Regulator mindset and the ability to see from the perspective of the requestor Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with Privacy/Risk reviews Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience engaging with external regulators or in an external engagement role Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Familiarity with adjacent compliance spaces such as Competition, Integrity, and Security Knowledge of Meta products and principlesMeta builds technologies that help people connect, find communities, and grow businesses. This role bridges the gap between engineering and compliance, requiring both technical depth (SQL, Python, Hack) and the ability to communicate findings clearly to external regulators and internal stakeholders including product, engineering, legal, and risk subject matter experts.