Senior Data Scientist

Senior Data Scientist – Product & Recommendations

About the Role

We’re looking for a Senior Data Scientist to take full ownership of how data shapes and optimizes a recommendations-first product experience. This is a rare opportunity to build and influence a data strategy from the ground up, directly impacting the way users discover and connect with meaningful content and people around the world. You’ll collaborate closely with product, engineering, and design teams to explore user behavior, design experiments, and make the product more personalized and impactful.

This role is ideal for someone who thrives in ambiguity—comfortable exploring open-ended questions, building metrics and dashboards, and working alongside ML and infrastructure teams to make continuous, data-driven improvements.

• Build and maintain dashboards and key performance metrics that empower the team to monitor performance and self-serve insights.

• Analyze user behavior, engagement patterns, and search data to uncover opportunities for product optimization.

• Partner with engineering to improve data organization and infrastructure, ensuring scalability and reliability.

• Design, execute, and evaluate A/B tests and other experiments to inform product strategy and measure feature impact.

• Leverage existing ML models and experimentation frameworks to enhance relevance, recommendations, and personalization.

• Apply and assess large language models (LLMs) for tasks like semantic search, personalization, and user understanding, while developing expertise in LLM evaluation best practices.

• Collaborate with ML engineers and infrastructure teams to refine recommendation systems and embedding pipelines.

• Champion a data-driven culture by clearly communicating findings and empowering stakeholders through accessible, actionable insights.

• 3+ years of experience in data science or analytics, ideally supporting product teams or user-facing applications.

• Experience working with recommendation systems, search ranking, or personalization algorithms is highly preferred.

• Strong proficiency in Python and SQL, with experience managing and analyzing large-scale datasets.

• Hands-on experience with modern data tools, such as dbt and Snowflake/Databricks for transformation;
  Mixpanel, Segment, or equivalent for event tracking; and Looker, Omni, or Tableau for visualization.

• Familiarity with machine learning libraries (e.g., Scikit-learn, XGBoost) and optional exposure to deep learning frameworks like PyTorch.

• Practical experience applying or evaluating LLMs in real-world, product-oriented contexts (e.g., search, recommendations, personalization).

• Strong analytical and experimental design skills, with the ability to translate complex findings into clear product insights.

• Effective communicator and collaborator who enjoys partnering with product managers, engineers, and designers.