Director, Collections Decision Science – Strategy

Role Overview

• Leads the design, deployment, optimization, and governance of predictive decisioning strategies supporting outbound collections operations
• Develops, validates, deploys, and optimizes predictive models supporting collections segmentation, prioritization, and treatment strategies
• Operationalizes machine learning and statistical models directly within collections and decisioning platforms
• Translates model outputs into executable decision logic, workflows, thresholds, routing rules, and contact strategies
• Monitors production model performance and recalibrates strategies based on drift, operational outcomes, regulatory changes, and portfolio behavior
• Designs and manages customer segmentation strategies aligned to delinquency stage, risk tiers, roll rates, payment behavior, and customer engagement patterns
• Defines and governs outbound contact policies, including channel prioritization, cadence strategies, suppression logic, quiet hours, and contact frequency limits
• Leads A/B and multivariate testing initiatives across messaging, channel mix, pacing, cadence, and strategy execution
• Partners with Dialer Operations and Workforce Management teams to optimize list generation, routing, pacing, penetration rates, and operational efficiency
• Develops and maintains executive-level reporting and dashboards measuring RPC, PTP, liquidation rates, cures, roll rates, recovery performance, and operational KPIs
• Maintains model governance documentation, change management controls, validation standards, audit readiness, and regulatory compliance support
• Collaborates cross-functionally with Compliance, Legal, Technology, Data Engineering, and Operations teams to ensure decision strategies remain compliant, scalable, and operationally effective
• Evaluates emerging technologies, decisioning capabilities, and analytics methodologies to continuously improve collections performance and customer outcomes.

Requirements

• Bachelor’s degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, Finance, Economics, or a related field, or commensurate work experience required
• 7 years of experience in decision science, collections strategy, credit risk analytics, or predictive modeling within a regulated financial services environment
• Hands-on experience developing and deploying predictive models into production decisioning or collections platforms
• Experience operationalizing machine learning models such as XGBoost, decision trees, logistic regression, or similar predictive methodologies
• Strong SQL skills with working knowledge of Python and/or R
• Experience with collections platforms, decision engines, or dialer orchestration tools such as Pega Collections, Debt Manager, Aspect, Genesys, Noble, or similar technologies
• Demonstrated experience designing and analyzing A/B testing and champion/challenger strategies in production environments
• Strong understanding of FDCPA, TCPA, CAN-SPAM, Regulation F, UDAAP, and applicable privacy regulations impacting collections operations
• Experience translating analytical insights into operational strategies and measurable business outcomes
• Strong communication and stakeholder management skills with the ability to influence cross-functional teams and executive leadership.

Tech Stack

• Python
• SQL

Benefits

• Health insurance
• Retirement plans