Staff Data Scientist - Experience

Lead analyses across user behavior and content data to shape product and strategy decisions.

Shape how we evaluate and improve content classification and taxonomy, with a particular focus on safety, combining analytical depth with a broader view of product and business needs.

Design evaluation frameworks, including sampling strategies, setting baselines, metrics, and annotation-based approaches, and guide how these methods are applied across the team.

Build scalable analytical foundations, including metrics, dashboards, and the data and context needed to enable effective self-serve analysis and agents.

Partner with Product, Engineering, and Operations leadership to shape priorities and how data informs product strategy.

Raise the analytical bar across Product Insights through methodological leadership, mentorship, and by identifying opportunities to improve how we work with data across domains.

You have deep experience as a product data scientist and have operated at Staff level or equivalent.

You have a strong foundation in statistics and experience designing evaluation and measurement approaches, including annotation-based methods and settings where controlled experiments are not feasible.

You have experience in building metrics and reporting systems that support product or policy decision-making.

You have built self-serve analytical tools or data agents that enable others to answer questions effectively.

You are proficient in SQL and experienced with Python, DBT, or similar tools for building and maintaining reliable analytical datasets

You leverage state of the art LLM models to do your analysis while ensuring quality and accuracy in the output

You communicate clearly across functions, influence decisions with senior stakeholders, and help raise analytical standards through mentorship and methodological leadership.

You have experience working on content classification, taxonomy, safety, policy, or adjacent domains where data quality and judgment are important to product decisions.