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Northbeam · 1 day ago

Director, Data Science

San Francisco, CA

Full-time

Hybrid

Director/Executive

$250K/yr - $300K/yr

8+ years exp

Northbeam is building the world's most advanced marketing intelligence platform, providing top eCommerce brands a unified view of their business data. The Director of Data Science leads complex technical initiatives, oversees the development of models and systems, and collaborates with cross-functional teams to drive innovation and measurement accuracy.

Information TechnologyMachine Learning

Responsibilities

Own and execute the technical roadmap for data science models and scalable, production-grade data products

Lead cross-functional initiatives end-to-end—from problem definition through launch—driving clear milestones, accountability, and high quality standards

Act as a true peer partner to Engineering, Product and Design, aligning on technical strategy, architectural decisions, and long-term roadmaps

Lead teams responsible for developing, validating, and productionizing models, working closely with Engineering to ensure the right data sources, pipelines, and APIs are in place

Hire, mentor, and develop top talent while continuously raising the bar through rigorous reviews, coaching, and feedback

Deeply understand customer pain points and desired outcomes; turn them into clear technical requirements and DS solution designs

Recommend and translate statistical outputs and data science models into customer-facing features and enterprise solutions

Establish repeatable validation processes for model release and collaborate with Data Engineering to ensure data quality and robust edge-case handling

Qualification

Data ScienceMachine LearningStatistical AnalysisPythonSQLRCausal InferenceTime Series AnalysisBayesian ModelingML Systems DeploymentStartup ExperienceCommunication SkillsTeam LeadershipMentoringPresentation Skills

Required

8+ years in data science or ML engineering roles, including 5+ years managing senior data scientists or technical leads

Demonstrated ability to hire, develop, and retain senior technical talent, while building and sustaining a high-performing, inclusive team culture

Master's degree (or equivalent experience) in statistics, econometrics, machine learning, or a related quantitative field

Strong foundation in causal inference, time series analysis, Bayesian modeling, and experimental design

Experience designing and deploying ML systems at scale in collaboration with engineering teams

Proficiency in Python, R, and SQL; experience with modern data platforms (e.g., BigQuery, Snowflake), MLOps practices, and pipeline orchestration tools

Strong communication skills with demonstrated excellence in translating complex statistical concepts for non-technical stakeholders

Thrives in a fast-moving startup environment, balancing rigor with speed and pragmatism

Cares deeply about your team and their long-term growth and success