Responsibilities
- 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 needed
Minimum Qualifications
- 4+ 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
Preferred Qualifications
- 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 principles
$153,000/year to $209,000/year + bonus + equity + benefits
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