Director, Collections Decision Science & Strategy

Aqua Finance, Inc.•Bartlett, TN

8d•Onsite

About The Position

The Director, Collections Decision Science & Strategy leads the design, deployment, optimization, and governance of predictive decisioning strategies supporting outbound collections operations across dialer, SMS, email, and digital engagement channels. This role combines advanced analytics, operational strategy, and production decisioning platform ownership to drive recovery performance, customer experience, and regulatory compliance. This leader is responsible for developing and operationalizing predictive models and decision logic within collections platforms such as Pega Collections, Debt Manager, and dialer orchestration systems. The role partners closely with Operations, Technology, Compliance, and Risk teams to deliver scalable, explainable, and compliant collections strategies aligned with FDCPA, TCPA, CAN-SPAM, Regulation F, UDAAP, and applicable privacy regulations.

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.

Responsibilities

Develop, validate, deploy, and optimize predictive models supporting collections segmentation, prioritization, and treatment strategies.
Operationalize machine learning and statistical models directly within collections and decisioning platforms, including Pega Collections, Debt Manager, and outbound dialer environments.
Translate model outputs into executable decision logic, workflows, thresholds, routing rules, and contact strategies.
Monitor production model performance and recalibrate strategies based on drift, operational outcomes, regulatory changes, and portfolio behavior.
Design and manage customer segmentation strategies aligned to delinquency stage, risk tiers, roll rates, payment behavior, and customer engagement patterns.
Define and govern outbound contact policies, including channel prioritization, cadence strategies, suppression logic, quiet hours, and contact frequency limits.
Lead A/B and multivariate testing initiatives across messaging, channel mix, pacing, cadence, and strategy execution.
Partner with Dialer Operations and Workforce Management teams to optimize list generation, routing, pacing, penetration rates, and operational efficiency.
Develop and maintain executive-level reporting and dashboards measuring RPC, PTP, liquidation rates, cures, roll rates, recovery performance, and operational KPIs.
Maintain model governance documentation, change management controls, validation standards, audit readiness, and regulatory compliance support.
Collaborate cross-functionally with Compliance, Legal, Technology, Data Engineering, and Operations teams to ensure decision strategies remain compliant, scalable, and operationally effective.
Evaluate emerging technologies, decisioning capabilities, and analytics methodologies to continuously improve collections performance and customer outcomes.