Why This Job is Featured on The SaaS Jobs
Forecasting sits at the heart of how subscription businesses run, and this Senior Data Scientist role is anchored in that reality. The remit spans revenue planning and long range strategy, positioning the work at the junction of product usage, customer behavior, and financial outcomes. In a SaaS company where recurring revenue and retention dynamics drive decision making, building forecasting systems is not a back office exercise but a core operating capability.
For a SaaS career, the standout value is end to end ownership of production grade modeling, from research and methodology through tooling, monitoring, and lifecycle management. The emphasis on uncertainty quantification, scenario simulation, and backtesting reflects the way mature SaaS organizations evaluate bets across pricing, go to market motions, and product adoption. Experience partnering with Finance, Product, and Sales also builds a transferable operating model for influencing roadmap and investment decisions with data.
This role fits a practitioner who prefers ambiguous problems with measurable business impact and enjoys raising technical standards across a team. It will suit someone comfortable translating executive planning questions into rigorous models, and who wants their data science work to be embedded in how a SaaS company allocates resources and sets targets.
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.
About the Team
The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates.
The Role
As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models.
What You’ll Do
Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting).
Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics.
Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulation.
Apply advanced statistical and ML techniques to model customer behavior, product adoption, revenue dynamics, and cost trends.
Drive improvements in automation, monitoring, drift detection, and lifecycle management of forecasting models.
Partner with Finance, Product, and Sales teams to quantify the impact of new initiatives and understand key business drivers.
Mentor and provide technical guidance to other data scientists; raise the bar for modeling rigor and production quality across the team.
What We’re Looking For
Advanced degree in a quantitative discipline (Statistics, Mathematics, Operations Research, Economics, Engineering, Computer Science) or equivalent practical experience.
8+ years of experience building and deploying production-grade ML or statistical systems, with significant experience in time-series modeling.
Deep expertise in probabilistic modeling, forecasting methodologies, and model evaluation techniques.
Strong proficiency in Python and the scientific Python ecosystem; fluency in SQL.
Experience designing systems for large-scale data processing (e.g., Snowflake, BigQuery, Redshift, Spark).
Demonstrated ability to lead technically ambiguous projects with significant business impact.
Excellent communication skills, with experience presenting complex quantitative findings to executive stakeholders.
A track record of elevating technical standards and mentoring other scientists.
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
