Build the future of data. Join the Snowflake team.

The Product Data Science team is looking for a Principal Full-stack Data Scientist to come aboard and be part of some of the foundational areas at Snowflake. In this role, you will work closely with our Product and Engineering teams on core operations and data privacy, security, and governance domains. You will also work on long-running analytical initiatives that will yield substantial product enhancements. This is a strategic, high-impact role that will help shape the future of Snowflake products and services.

AS A PRINCIPAL FULL STACK DATA SCIENTIST AT SNOWFLAKE YOU WILL:

• Be a proactive partner to Product Management and Engineering to shape feature roadmaps and help design metrics and analytical workflows to evaluate their success and effectiveness.  
• Architect efficient data models and high quality production pipelines and partner with Engineering for all necessary telemetry. 
• Build scalable and extensible analytics/ML frameworks to uncover feature usage patterns, subtle issues with the system, potential performance enhancements, and areas to improve customer experience.
• Be an early adopter/pro user of Snowflake features and provide feedback on design parameters.  
• Evaluate the right surface (Snowflake Notebook/Worksheet/Snowsight Dashboards/Streamlit Apps) to disseminate your insights for maximal impact. 
• Influence decisions and drive initiatives with the Product Management and Engineering teams to drive better outcomes for our customers.
• Answer questions from the executive team for reporting to the board and contribute to industry reports and similar publications.
• Think creatively and be scrappy to find optimal solutions to our complex, often unstructured problems.

OUR IDEAL CANDIDATE WILL HAVE:

• MS/Ph.D. in quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS). 
• 12+ years of relevant data science or related experience.    
• Expert-level experience working with SQL & Python including scikit-learn, numpy, and pandas.
• Expert in working with large-scale machine generated data (e.g., logs, application telemetry, or customer usage data).
• High fluency with MPP databases, such as Snowflake, Redshift, BigQuery, Vertica, etc. 
• Expert data-driven storytelling skills to convey insights to business leaders and technical stakeholders and influence decisions. 
• The ability to thrive in a dynamic environment, being flexible and willing to jump in and do whatever it takes to contribute to the success of your area.