Principal Data Scientist - Advanced Analytics

Vericast is investing in the next generation of Advanced Analytics, Experimentation, and Measurement, and we're looking for a Principal Data Scientist to help lead the way. This is a highly visible opportunity for a data science leader who thrives at the intersection of experimentation, causal inference, machine learning, and Generative AI.In this role, you'll shape our analytics discipline from the ground up, partnering with executive leaders and cross-functional teams to solve complex business challenges with data. You'll design rigorous experimentation frameworks, build and deploy scalable AI and machine learning solutions, and transform complex insights into clear recommendations that drive growth and measurable business impact.This is a senior individual contributor role that offers the opportunity to influence strategy, establish best practices, mentor other data scientists, and leave a lasting mark on how Vericast leverages data to make decisions.What You'll DoLead Experimentation & Measurement Strategy (40%)Own the end-to-end design, execution, and analysis of marketing and product experiments, including A/B, multivariate, geo, and holdout testing.Define and manage the experimentation roadmap, including hypothesis development, prioritization, power analysis, and success metrics.Develop and refine methodologies for lift measurement, incrementality testing, and causal inference.Establish standards, governance, and best practices that ensure statistical rigor and actionable insights across the organization.Partner with stakeholders to build a culture of experimentation and data-driven decision making.Drive Advanced Analytics, Machine Learning & GenAI Innovation (40%)Design, build, validate, and deploy machine learning and Generative AI solutions using large-scale structured and unstructured data.Develop predictive, prescriptive, attribution, market mix, and uplift models that drive measurable business outcomes.Lead hands-on model development, coding, testing, and production deployment while establishing technical standards for the broader team.Create and maintain robust data pipelines to ensure data quality, integrity, and scalability.Continuously evaluate emerging technologies and analytical approaches to improve performance and business value.Influence the Business Through Strategic Partnership (20%)Collaborate with Product, Marketing, Sales, IT, Risk, and Compliance teams to identify, prioritize, and solve high-value business opportunities.Translate complex business challenges into testable hypotheses and analytical solutions.Present findings and recommendations to both technical and executive audiences in a clear and compelling way.Serve as a trusted advisor and subject matter expert on experimentation, analytics, AI, and machine learning.Mentor and elevate fellow data scientists through coaching, technical guidance, and best-practice sharing.