Define and own the enterprise decisioning charter, objectives, operating model, guardrails (e.g., prospect and existing client fatigue, fairness, privacy), and KPI trees aligned to strategic business outcomes.
Establish and govern the enterprise roadmap for the decision engine, including prioritization of NBA and lead-routing initiatives in partnership with Sales, Marketing, Product, Technology, and Client Services.
Balance delivery commitments, technical constraints, and strategic trade-offs while communicating clear timing, dependencies, and risks to executive stakeholders.
Maintain end-to-end accountability for the architecture, build, performance, governance, and lifecycle management of a real-time decision engine powering NBA decisions and decision sequences at scale.
Direct teams responsible for translating enterprise goals (e.g., sales growth, engagement, retention) into eligibility schemas, fatigue and frequency limits, fairness constraints, reward functions, and constrained optimization approaches (assignment, pacing, routing).
Oversee the design and deployment of decision policies, optimization frameworks, and sequencing logic that deliver the best action or action sequence for each prospect or existing client.
Establish standards for experimentation, rollout, and risk management, incorporating canaries, bandit approaches, A/B testing, and statistically sound ship/iterate/stop decisions.
Partner with personalization, experimentation, and analytics leaders to co-own experimentation strategy, learning agendas, and measurement frameworks.
Lead cross-functional technology delivery by setting requirements and direction for real-time decision APIs, integrations, rules engines, data models, and logging frameworks.
Ensure enterprise standards for versioning, audit trails, rollback and disaster recovery plans, incident response, and service-level agreements.
Maintain canonical decision metrics, fairness and eligibility checks, transparent decision logs, and audit-ready documentation to support reporting, regulatory review, and internal governance.
Build, lead, and develop a team of Decision Science and Technical Product Management leaders; set expectations, coach performance, and grow enterprise decisioning capabilities.

Requirements

Bachelor’s degree in Computer Science, Engineering, Business, or a related field required; MBA or advanced degree preferred.
9 + years of experience in decision science, applied data science, optimization, or equivalent fields.
3+ years of experience leading managers or senior practitioners in a people management capacity.
Proven leadership in the design, delivery, and governance of enterprise-scale, real-time decisioning and decision policy systems.
Deep expertise in optimization and experimentation techniques, including uplift modeling, bandits, experimental design, generalized linear models, allocation models, and related approaches.
Strong proficiency in SQL and Python, with the ability to guide technical standards and review work at scale.
Experience directing teams that build or integrate real-time, API-driven decisioning platforms.
Strong business and financial acumen, with demonstrated executive communication skills and ability to influence senior leaders.
Strategic thinker capable of balancing near-term delivery with long-term platform and capability vision.
Demonstrated success shipping and operating decision or rules engines in production, including integration with feature stores and model registries.
Experience overseeing experimental design and measurement practices across teams.
Strong intuition for end-customer needs and behaviors, and the ability to translate insights into scalable decision strategies.
Demonstrated ability to navigate complex, matrixed organizations to drive enterprise priorities.
Working curiosity and applied understanding of emerging artificial intelligence (AI) capabilities and their impact on decisioning, optimization, and governance.

Benefits

Medical, dental, vision and life insurance
Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
Tuition reimbursement up to $5,250/year
Business-casual environment that includes the option to wear jeans
Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
Paid volunteer time — 16 hours per calendar year
Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

decision scienceapplied data scienceoptimizationSQLPythonuplift modelingbanditsexperimental designgeneralized linear modelsAPI-driven decisioning

Soft Skills

leadershipexecutive communicationstrategic thinkinginfluenceteam developmentperformance coachingbusiness acumenproblem-solvingcollaborationadaptability

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringBachelor’s degree in BusinessMBAadvanced degree