Principal Data Scientist, Northbeam

• 8+ years in data science or ML engineering roles
• PhD (or equivalent experience) in statistics, econometrics, machine learning, or a related quantitative field, with a strong foundation in causal inference, experimental design, and Bayesian modeling
• Proven experience applying statistical methods to marketing measurement, attribution modeling, and related incrementality/experiment design problems
• Experience in building or optimizing large-scale A/B testing or experimentation infrastructure
• Experience designing, deploying, and operating statistical/ML models that drive real business decisions at scale, including validation and monitoring
• Proficiency in Python/R/SQL and modern data platforms (BigQuery, Snowflake), familiarity with MLOps practices and data pipeline orchestration tools
• Strong communication skills, with the ability to explain complex statistical concepts to customers and internal stakeholders, translating technical nuance into business confidence

Desirable

• We are seeking a Principal Data Scientist to own the science behind how we measure marketing effectiveness at scale
• You will turn ambiguous attribution problems into reliable systems that drive confident business decisions, both across our organization and for our customers
• This is a hands-on technical lead role where you'll advance the state-of-the-art in marketing measurement while ensuring our current systems deliver exceptional accuracy and reliability
• You will serve as the technical architect for attribution methodologies, experiment design, and statistical inference—balancing cutting-edge research with practical business impact
• Working closely with engineering teams, you'll drive both the optimization of existing attribution systems and the development of next-generation capabilities including AI-powered measurement techniques
• Own and advance the statistical foundations of marketing-effectiveness measurement, ensuring methodologies are robust, reliable, and scalable
• Research, prototype, and deploy advanced attribution and AI models for marketing measurement
• Design and evolve complex data science models that balance scientific rigor with practical, scalable frameworks
• Build and maintain experimentation frameworks for model validation and lift measurement
• Define and implement validation and release criteria for attribution model and product launches, including data-quality checks, model benchmarking, and validation metrics
• Collaborate with Software Engineers and Product Managers to (respectively) productionize and productize your work
• Mentor Data Scientists on complex statistical and methodological challenges, including experiment design; raise the bar for individual execution via reviews and training