Principal Data Scientist

Principal Data Scientist – Bayesian Modeling (Marketing Mix Modeling) Contract: 12 months Pay Rate: $80–$90/hour Location: Fully Remote Role Overview We are seeking a highly skilled and communicative Principal Data Scientist to lead the development of a Bayesian Marketing Mix Modeling (MMM) MVP for a high-profile client. This role is hands-on and highly visible, requiring deep statistical expertise, ownership of modeling decisions, and the ability to clearly translate complex insights to both technical and non-technical stakeholders. The ideal candidate is comfortable leading modeling efforts end-to-end, collaborating across teams, and delivering production-ready models in a cloud environment (likely Azure). Important Note: This role must not be staffed with individuals affiliated with PyMC (e.g., core contributors, maintainers, or individuals officially representing PyMC in a professional capacity). Key Responsibilities • Lead the design, development, and implementation of Bayesian Marketing Mix Models using PyMC or NumPyro • Own the full modeling lifecycle, including data preparation, model architecture, fitting, validation, and interpretation • Serve as the primary modeling lead, making independent decisions on statistical approach and trade-offs • Partner with internal teams and client stakeholders to align modeling outputs with business objectives • Clearly communicate technical concepts, assumptions, and results to audiences ranging from data scientists to executives • Guide and mentor team members on Bayesian modeling best practices and statistical reasoning Required Qualifications • Proven hands-on experience delivering Marketing Mix Models (MMM) using Bayesian techniques • Strong proficiency in Bayesian programming frameworks (PyMC and/or NumPyro) • Deep understanding of Bayesian statistics, probabilistic programming, and time-series analysis • Experience working in cloud environments, preferably Azure, for data science workflows • Excellent verbal and written communication skills, with the ability to explain complex models in plain language • Demonstrated ownership of modeling initiatives in fast-moving or ambiguous project environments Preferred Qualifications • Background in client-facing, consulting, or MVP-driven engagements • Familiarity with modern MLOps practices and Git-based collaboration workflows • Experience operating as a technical lead or principal-level contributor