Define and own the enterprise decisioning charter, objectives, operating model, guardrails, and KPI trees aligned to strategic business outcomes, including prospect and existing client fatigue, fairness, and privacy.
Establish and govern the enterprise roadmap for the decision engine, including prioritization of next-best-action 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 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 next-best-action decisions and decision sequences at scale.
Direct teams responsible for translating enterprise goals, such as sales growth, engagement, and retention, into eligibility schemas, fatigue and frequency limits, fairness constraints, reward functions, and constrained optimization approaches.
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, and 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
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 the ability to influence senior leaders
Strategic thinking skills, with the ability to balance 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 capabilities and their impact on decisioning, optimization, and governance.
Tech Stack
Python
SQL
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.