Principal Data Scientist, Marketing Analytics and Data Science (Hybrid)

About the Role

Key Responsibilities

• Lead the design, validation, and continuous improvement of MMM solutions, collaborating with vendors and internal teams to ensure scalable, accurate, and business-aligned models.
• Work closely with marketing, finance, and media teams to align modeling efforts with business objectives and ensure insights are relevant and actionable.
• Champion data integrity, model validation, and methodological innovation, staying ahead of industry trends in MMM, MTA, and causal inference.
• Design robust testing frameworks to evaluate model reliability pre- and post-deployment.
• Support the integration of MMM with other measurement approaches (e.g., MTA) to enable a unified view of marketing performance.
• Translate complex business challenges into structured analytical approaches, collaborating with analysts and stakeholders to ensure alignment with strategic goals.
• Mentor junior team members, promote modeling standards, and foster a culture of excellence and continuous learning.
• Extend MMM frameworks to include donor experience, bequests, and internal investments.
• Co-lead the design of ALSAC's What-If Scenario Simulator for strategic planning.
• Contribute to AI agent and GenAI tool development for donor intelligence and scenario planning.
• Implement model governance, version control, and explainability tools (e.g., SHAP, LIME).

Requirements

• Bachelor's degree in Statistics, Economics, Computer Science, or related quantitative field.
• 10+ years of experience in marketing analytics, data science, or econometric modeling, with a focus on MMM.
• Advanced degree (Master's or PhD) strongly preferred.
• Demonstrated success in enterprise-scale modeling and strategic analytics leadership.
• Expertise in advanced modeling and causal inference techniques such as MTA, Bayesian modeling, Markov chains, SEM, survival analysis, DiD, synthetic control, BART.
• Experience building modular forecasting pipelines with elasticity-aware logic and designing scenario simulators with constraints and real-time feedback.
• Proficiency in translating complex outputs into executive-ready insights and presenting to senior leadership.
• Deep understanding of feature engineering, temporal alignment, data lineage, and collaboration with ML engineers and MLOps teams.
• Experience working with structured/unstructured data across CRM, media, finance, and APIs.

Nice to Have

• Experience with ensemble models, neural networks, and meta-modeling.
• Familiarity with AI and GenAI tools for donor intelligence and scenario planning.
• Knowledge of model governance, version control, and explainability tools like SHAP and LIME.

Qualifications

• Bachelor's degree in Statistics, Economics, Computer Science, or related field.
• 10+ years of relevant experience in marketing analytics or data science.
• Advanced degree (Master's or PhD) preferred.

Benefits & Perks

• Core Medical Coverage: Low-cost, low-deductible Medical, Dental, and Vision Insurance plans.
• 401K Retirement Plan with 7% Employer Contribution.
• Exceptional Paid Time Off.
• Maternity / Paternity Leave.
• Infertility Treatment Program.
• Adoption Assistance.
• Education Assistance.
• Enterprise Learning and Development.