Senior Director, Decision Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Define and take ownership of the enterprise decisioning charter, objectives, operating model, guardrails, and KPI trees to align with strategic business outcomes, encompassing prospect and existing client fatigue, fairness, and privacy.

• Establish and oversee the enterprise roadmap for the decision engine, prioritizing next-best-action and lead-routing initiatives in collaboration with Sales, Marketing, Product, Technology, and Client Services.

• Manage delivery commitments, technical limitations, and strategic trade-offs while effectively communicating timing, dependencies, and risks to executive stakeholders.

• Maintain comprehensive accountability for the architecture, development, performance, governance, and lifecycle management of a real-time decision engine that powers next-best-action decisions and decision sequences at scale.

• Lead teams tasked with translating enterprise objectives, such as sales growth, engagement, and retention, into eligibility schemas, fatigue and frequency limits, fairness constraints, reward functions, and constrained optimization methodologies.

• Supervise the design and implementation of decision policies, optimization frameworks, and sequencing logic that yield the optimal action or action sequence for each prospect or existing client.

• Set standards for experimentation, rollout, and risk management, incorporating canaries, bandit approaches, A/B testing, and statistically sound strategies for ship, iterate, and stop decisions.

• Collaborate with leaders in personalization, experimentation, and analytics to co-own the experimentation strategy, learning agendas, and measurement frameworks.

• Spearhead cross-functional technology delivery by specifying requirements and direction for real-time decision APIs, integrations, rules engines, data models, and logging frameworks.

• Guarantee 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 cultivate a team of Decision Science and Technical Product Management leaders; set expectations, coach performance, and enhance enterprise decisioning capabilities.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Business, or a related field.

• Over 9 years of experience in decision science, applied data science, optimization, or related fields.

• More than 3 years of experience in a people management role, leading managers or senior practitioners.

• Demonstrated leadership in designing, delivering, and governing enterprise-scale, real-time decisioning and decision policy systems.

• In-depth expertise in optimization and experimentation techniques, including uplift modeling, bandits, experimental design, generalized linear models, allocation models, and related methodologies.

• Strong proficiency in SQL and Python, with the capability to guide technical standards and review work at scale.

• Experience in directing teams that build or integrate real-time, API-driven decisioning platforms.

• Solid business and financial acumen, with proven executive communication skills and the ability to influence senior leaders.

• Strategic thinking abilities, capable of balancing near-term delivery with long-term platform and capability vision.

• Proven success in shipping and operating decision or rules engines in production, including integration with feature stores and model registries.

• Experience in overseeing experimental design and measurement practices across teams.

• Strong intuition for end-customer needs and behaviors, with the ability to translate insights into scalable decision strategies.

• Demonstrated ability to navigate complex, matrixed organizations to drive enterprise priorities.

• A working curiosity and applied understanding of emerging artificial intelligence capabilities and their implications for 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.