Director of Strategic Analytics

Role Overview

• Set the strategic direction for advanced analytics within EFCC, with an emphasis on AI, machine learning, and scalable cloud architectures.
• Lead and develop a high-performing analytics team spanning emerging risk analytics, quantitative modeling, and data intelligence.
• Translate regulatory expectations, emerging typologies, and business needs into analytically sound, defensible solutions.
• Oversee development and enhancement of customer
• and account-level risk models, anomaly detection, and typology-driven analytics.
• Expand use of machine-learning frameworks and AI-enabled tooling (e.g., clustering, relationship intelligence, natural-language analysis) to surface risk not fully covered by traditional monitoring.
• Guide iterative model improvement using new data sources, feedback loops from investigations, and performance metrics.
• Remain hands-on as needed to unblock team members, prototype solutions, and credibly challenge analytical assumptions.
• Assist in driving the transition from legacy statistical tooling toward open-source and cloud-ready solutions, improving flexibility and speed to insight.
• Support development of open-source equivalents for existing analytics and reporting capabilities to enable future cloud adoption.
• Coordinate rapid-response analytics for emerging financial crime risks, integrating subpoena data, human intelligence, transaction data, and external insights.
• Lead analytics supporting new and evolving typologies (e.g., novel fraud schemes, sanctions evasion, trafficking-related activity).
• Maintain strong feedback cycles with investigators and risk partners to refine coverage and prioritize effort.
• Ensure clear, consistent documentation across analytics lifecycles, including model design, assumptions, validation artifacts, monitoring reports, and procedures.
• Communicate complex analytical concepts clearly to executive leadership, regulators, auditors, and cross-functional partners.
• Represent Strategic Analytics in regulatory exams, internal reviews, and enterprise-level discussions.

Requirements

• Bachelor’s degree required; advanced degree (MS/PhD) strongly preferred.
• 9+ years of experience in advanced analytics, quantitative modeling, or data science within financial services or regulated environments.
• 5+ years of experience leading analytics or quantitative teams.
• Strong grounding in statistical modeling, machine learning, and model performance evaluation.
• Experience working with open-source analytics stacks (e.g., Python-based ecosystems) and designing analytics for cloud or cloud-adjacent environments.
• Ability to integrate structured and unstructured data, including transaction data and narrative-based intelligence.
• Deep understanding of financial crime risk, emerging typologies, and risk-based monitoring approaches.
• Strong familiarity with regulatory expectations, supervisory guidance, and model governance standards.
• Experience supporting regulatory exams and translating analytics into examiner-ready narratives.
• Demonstrated ability to operate at both strategic and execution levels.
• Proven success influencing across teams without direct authority.
• Clear, confident communicator with executive presence and strong written skills.

Tech Stack

• Cloud
• Python

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law