At ALSAC you do more than make a living; you make a difference.

We like people who are different…because we’re different, too. As one of the world’s most iconic and respected nonprofits, we know what it’s like to stand out. That’s why we’re looking at you. Your background, perspective, and desire to make an impact set you apart. As we work to help St. Jude cure childhood cancer, we're calling on the game-changers, innovators and visionaries to join our family. Not just for the kids of St. Jude, but also for you. Because at ALSAC, we develop and celebrate our employees. So, bring your whole, authentic self and become part of our shared mission: Finding cures. Saving children.®

Job Description

ALSAC is seeking a visionary Principal Data Scientist to lead the development and evolution of our Marketing Mix Modeling (MMM) capabilities within a newly formed Marketing Analytics and Data Science team. This net-new role offers a unique opportunity to shape enterprise-wide measurement frameworks, drive strategic planning through scenario simulation, and pioneer AI-driven innovation in donor intelligence.

As a senior individual contributor, you will provide technical leadership, collaborate with external vendors in a build-operate-transfer model, and mentor junior data scientists. You’ll translate complex business questions into actionable analytical frameworks, ensuring modeling outputs are both rigorous and aligned with strategic goals.

Key Responsibilities

1. MMM Capability Ownership
Lead the design, validation, and continuous improvement of MMM solutions. Collaborate with vendors and internal teams to ensure scalable, accurate, and business-aligned models.

2. Cross-Functional Partnership
Work closely with marketing, finance, and media teams to align modeling efforts with business objectives and ensure insights are relevant and actionable.

3. Model Quality & Innovation
Champion data integrity, model validation, and methodological innovation. Stay ahead of industry trends in MMM, MTA, and causal inference.

4. Testing & Experimentation Strategy
Design robust testing frameworks to evaluate model reliability pre- and post-deployment.

5. Integrated Measurement Strategy
Support integration of MMM with other measurement approaches (e.g., MTA) to enable a unified view of marketing performance.

6. Analytical Framework Development
Translate complex business challenges into structured analytical approaches. Collaborate with analysts and stakeholders to ensure alignment with strategic goals.

7. Mentorship & Best Practices
Mentor junior team members, promote modeling standards, and foster a culture of excellence and continuous learning.

Top Skills & Experience

I. Advanced Modeling & Causal Inference

• Expertise in MTA, Bayesian modeling, Markov chains, SEM, and survival analysis.
• Skilled in causal inference techniques (DiD, synthetic control, BART).
• Ability to tailor models to varying data richness across channels.

II. Enterprise-Scale Forecasting & Simulation

• Experience building modular forecasting pipelines with elasticity-aware logic.
• Skilled in designing scenario simulators with constraints and real-time feedback.
• Familiarity with ensemble models, neural networks, and meta-modeling.

III. Strategic Insight & Stakeholder Engagement

• Proven ability to translate complex outputs into executive-ready insights.
• Experience presenting to senior leadership and crafting strategic narratives.
• Skilled in communicating uncertainty and scenario governance.

IV. Data Engineering Fluency

• Deep understanding of feature engineering, temporal alignment, and data lineage.
• Experience collaborating with ML engineers and MLOps teams.
• Proficient in working with structured/unstructured data across CRM, media, finance, and APIs.

Additional Impact Areas

• Enterprise-Wide Modeling: Extend MMM frameworks to include donor experience, bequests, and internal investments.
• Scenario Simulation Leadership: Co-lead the design of ALSAC’s What-If Scenario Simulator for strategic planning.
• AI & GenAI Innovation: Contribute to AI agent and GenAI tool development for donor intelligence and scenario planning.
• Governance & Transparency: Implement model governance, version control, and