Why This Job is Featured on The SaaS Jobs
This Senior Data Scientist role sits at the intersection of product decision-making and applied machine learning inside a mature, data-intensive SaaS platform. In the current SaaS landscape, where usage telemetry and self-serve adoption loops increasingly shape roadmaps, the mandate to partner tightly with Product and Engineering signals work that is embedded in how the product evolves, not separated into a reporting function.
For a long-term SaaS career, the position offers repeated exposure to the mechanics of product analytics at scale: defining success metrics, improving instrumentation, and translating behavioral data into changes that ship. The emphasis on production pipelines and extensible frameworks aligns with a growing expectation in SaaS that data science contributions are operational, reproducible, and measurable over time. Experience communicating outcomes to senior stakeholders also maps well to progression into staff-level analytics leadership or product-facing data roles.
The role is best suited to someone who enjoys ambiguity in problem definition, can move between deep technical execution and cross-functional influence, and is motivated by iterative product improvement. It will fit professionals who prefer working close to engineering systems and customer usage signals, and who want their analysis to directly inform prioritization and launches.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
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.
OUR IDEAL CANDIDATE WILL HAVE:
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
