As a Data & AI Control Manager within the Strategic Control Testing group in OCM, you design and execute datadriven 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 auditready 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 endtoend 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 highquality reporting and executive summaries on trends, systemic issues, and control weaknesses.
- Stay current on LLMs/GenAI and advanced ML identify highvalue use cases with appropriate guardrails.
- Design statistical tests and MLbased 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 handson 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.
