Where Data Does More. Join the Snowflake team.
The Product Data Science team is looking for a Full-stack Senior Data Scientist to come aboard and be part of Snowflake’s most critical initiatives. In this role, you will work closely with our Product and Engineering teams on everything from core operations, to innovative AI/ML tools, to our fastest-growing new and experimental features. You will work on long-running analytical initiatives yielding substantial product enhancements. This is a strategic, high-impact role that will help shape the future of Snowflake products and services.
PLEASE NOTE: The position level is determined during the interview process and is influenced by various factors, including experience, educational attainment, skill level requirements, and overall interview performance.
AS A SENIOR 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.
Build efficient data models and high quality production pipelines and partner with Engineering for all necessary telemetry.
Build scalable and extensible analytics/ML/causal inference 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.
MS/Ph.D. in quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS).
8+ 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.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
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What We Do
Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.
Why Work With Us
Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.
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