Principal Data Scientist – Product

Key Responsibilities:

• Collaborate closely with Product Management and Engineering to shape feature roadmaps, define key metrics, and design analytical workflows for measuring success.
• Develop efficient data models and build high-quality production pipelines, ensuring proper telemetry in partnership with Engineering.
• Design and implement scalable analytics, machine learning, and causal inference frameworks to uncover feature usage patterns, detect system issues, enhance performance, and improve customer experience.
• Act as an early adopter and power user of Snowflake features, providing critical feedback on design and usability.
• Identify the most effective surface for sharing insights (e.g., Snowflake Notebook, Worksheet, Snowsight Dashboards, or Streamlit Apps) to maximize impact.
• Influence strategic decisions by working closely with Product Management and Engineering to drive better customer outcomes.
• Provide data-driven insights to the executive team for board reporting and contribute to industry reports.
• Think creatively and leverage innovative approaches to solve complex, unstructured problems effectively.

Ideal Candidate Qualifications:

• MS or Ph.D. in a quantitative discipline such as Mathematics, Statistics, Operations Research, Economics, Engineering, or Computer Science.
• 12+ years of experience in data science or a related field.
• Expert-level proficiency in SQL & Python, including libraries such as scikit-learn, NumPy, and pandas.
• Extensive experience working with large-scale machine-generated data (e.g., logs, application telemetry, or customer usage data).
• Deep knowledge of MPP databases, including Snowflake, Redshift, BigQuery, and Vertica.
• Exceptional data-driven storytelling skills to effectively communicate insights to business leaders and technical teams, influencing strategic decisions.
• Ability to thrive in a fast-paced environment, demonstrating flexibility and adaptability in tackling challenges.
  

  ---

  APPLY