Data and AI Control Manager

As a Data & AI Control Manager within the Strategic Control Testing group in OCM, you design and execute data‑driven control testing across Client Onboarding & Documentation, including WKO and DDS. You build automation and apply AI/ML—including Generative AI—to enhance risk detection, continuous monitoring, and regulatory compliance. You partner across businesses and Corporate Functions to close control gaps, uplift resilience, and maintain audit‑ready evidence.

Job Responsibilities 

• Lead strategic control testing engagements using analytics to surface gaps and BAU breaks; drive actionable remediation.
• Build and productionize AI/ML solutions (classification, anomaly detection, risk scoring, entity resolution) and GenAI workflows.
• Automate end‑to‑end testing and control processes with Alteryx, Power BI/Tableau, and workflow/RPA platforms.
• Operationalize proactive alerts and dashboards for KRIs and regulatory priorities.
• Partner with WKO, DDS, Controls, Operations, Technology, and Data teams to define requirements and ensure explainability/auditability.
• Maintain high‑quality reporting and executive summaries on trends, systemic issues, and control weaknesses.
• Stay current on LLMs/GenAI and advanced ML; identify high‑value use cases with appropriate guardrails.
• Design statistical tests and ML‑based monitors for policy, legal, and regulatory compliance aligned to audit and model risk governance.
• Build pipelines to ingest, profile, cleanse, and join large datasets from systems of record for repeatable analytics.
• Apply LLMs/GenAI for document parsing, policy mapping, and exception narrative synthesis using RAG and prompt engineering.
• Translate KYC/CO&D requirements into measurable tests and rules; tune to reduce false positives and document methods for audits.

Required Qualifications, Capabilities, and Skills 

• Hold a bachelor’s or advanced degree in a quantitative field (Computer Science, Statistics, Engineering, Data Science).
• Bring 6+ years in risk management/financial services across compliance, financial crimes, operational risk, audit, or BPM with automation/modeling exposure.
• Demonstrate proficiency in Python or R for data manipulation, model development, and testing automation at scale.
• Apply modern ML, pattern recognition, and statistical analysis with clear understanding of limitations in regulated environments.
• Consume APIs and integrate diverse data sources while adhering to data governance, lineage, and quality standards.
• Execute control testing with strong control design, root cause analysis, and documentation discipline.
• Partner across business, operations, and technology to deliver measurable risk and control outcomes.

Preferred Qualifications, Capabilities, and Skills 

• Leverage hands‑on experience with LLMs/GenAI and ML techniques for predictive modeling and monitoring.
• Utilize advanced analytics (regression, classification, clustering, dimensionality reduction) to improve control effectiveness.
• Manage 2–3 automation initiatives concurrently across global teams and time zones with clear governance.
• Strengthen compliance by aligning evidence to audit and model risk standards and ensuring explainability.
• Enhance data reliability via metadata, lineage tracking, and secure usage aligned to regulatory requirements.
• Communicate complex findings through concise executive summaries, dashboards, and stakeholder forums.
• Institutionalize lessons learned via playbooks, standardized test scripts, and reusable control components.