Senior Data Scientist - Product

Snowflake is hiring a Senior Data Scientist - Product in Menlo Park, United States. It pays $168k-$221k a year and Level rates it ; you can apply on Snowflake.

Level's read on this job

Works on AI ●●●○ is how Level rates this data scientist role: the daily work is on AI products, without building the model.
Pay on this posting starts in line with the typical data scientist posting on Level.
The posting mentions scikit-learn among its tools and skills.
Level classes it as a senior role.
Snowflake has 353 other open roles on Level.

AI in this role

scikit-learn

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

How we rate this

Senior Data Scientist - Product at Snowflake rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Data Scientist - Product is an open job at Snowflake.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $168k-$221k a year.
The role is based in US-CA-Menlo Park.
The job was posted on August 27, 2025.
Seniority: senior.
Applications are handled by Snowflake. Apply on Snowflake

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

scikit-learn

Also common in data scientist jobs at this level

Machine learning LLM Generative AI dbt Snowflake Spark

Pay

This job starts at: $168k
Typical data scientist job: $166k

This posting starts close to the typical data scientist job. See data scientist jobs

Questions you could be asked

What's a project where you used scikit-learn hands-on?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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