Director of Data Science

8+ years in data science or ML engineering roles, including 5+ years managing senior data scientists or technical leads. Proven ability to hire, develop, and retain senior technical talent while maintaining a high-performing 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; skilled at influencing without direct authority and partnering with engineering, product, and business stakeholders to drive success. Proficiency in Python, R, and SQL; experience with modern data platforms (e.g., BigQuery, Snowflake), MLOps practices, and pipeline orchestration tools. Proven ability in shaping data infrastructure requirements, aligning with product teams Strong communication skills with demonstrated excellence in translating complex statistical concepts for non-technical stakeholders.

Own the execution of the technical roadmap for data science models and scalable data products. Lead cross functional projects end-to-end—from scoping to launch—with clear milestones, accountability, and quality standards. Partner with Engineering and Product to align on milestones, unblock teams, and ensure execution velocity. Hire, mentor, and develop top talent while raising the execution quality through effective reviews and coaching. 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.