Northbeam is building the world’s most advanced marketing intelligence platform, providing top eCommerce brands a unified view of their business data through powerful attribution modeling and customizable dashboards. Our technology helps customers accurately track ad spend, understand the full customer journey, and drive profitable growth.
Requirements
- 8+ years in data science or ML engineering roles.
- 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.
- Experience in enterprise Martech, AdTech, B2B SaaS, or adjacent industries dealing with complex attribution challenges.
- Experience with identity resolution across web, mobile, and offline channels.
Responsibilities
- 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.
Other
- 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.
- Strong communication skills, with the ability to explain complex statistical concepts to customers and internal stakeholders, translating technical nuance into business confidence.
- Background with graph neural networks, deep learning applications.
- flexible PTO policy, 12 company-paid holidays, and 12 weeks of paid parental leave.
- $500 work-from-home stipend to support your remote setup.
