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.

Data and AI Control Manager