FAQs
What is the role of a Senior Data Scientist at Snowflake?
The Senior Data Scientist at Snowflake will drive high-impact initiatives for the global data application architecture, analyze large amounts of data to uncover patterns and issues, collaborate with Engineering and Product teams, build data pipelines and frameworks, monitor system performance, and provide data-driven insights to inform product decisions.
What qualifications does the ideal candidate for Senior Data Scientist at Snowflake have?
The ideal candidate will have an MS/Ph.D. in a quantitative discipline, expert-level experience with SQL and relational data, proficiency in Python, experience with large-scale machine-generated data, fluency with MPP databases, the ability to communicate data insights to both business and technical stakeholders, flexibility in a dynamic environment, and prior experience in data applications and marketplaces.
What are some key responsibilities of a Senior Data Scientist at Snowflake?
Key responsibilities include driving initiatives for data application architecture, analyzing data to uncover patterns and issues, working closely with Engineering and Product teams, building data pipelines and frameworks, monitoring system performance, providing data-driven insights for product decisions, and answering questions from the executive team.
What kind of projects can a Senior Data Scientist at Snowflake expect to work on?
A Senior Data Scientist at Snowflake can expect to work on long-running analytical initiatives with greater complexity and less structure, as well as projects focused on uncovering feature-usage patterns, system issues, performance enhancements, and user experience improvements. They may also work on creating data apps, dashboards, and analytical frameworks to monitor system performance.