Why This Job is Featured on The SaaS Jobs
Forecasting and revenue planning sit at the core of how SaaS companies steer product investment, sales capacity, and long-range strategy, and this role is positioned directly in that control loop. The focus on production-grade forecasting systems signals work that goes beyond ad hoc analysis into durable internal platforms, a hallmark of mature SaaS operators managing recurring revenue at scale. The remit also spans customer behavior, adoption, and cost dynamics, reflecting how subscription businesses need models that connect usage and go to market activity to financial outcomes.
For a SaaS career, the long-term value is in building a repeatable toolkit for turning ambiguous commercial questions into measurable, model-driven decisions. Experience with time-series rigor, uncertainty quantification, and scenario simulation transfers across SaaS contexts, from usage-based pricing to expansion forecasting. Close partnership with Finance, Product, and Sales also develops the cross-functional fluency that senior analytics leaders in SaaS are expected to bring.
This role tends to suit data scientists who prefer ownership of end-to-end modeling initiatives, including evaluation, monitoring, and lifecycle management. It fits professionals comfortable translating executive-facing planning needs into technical roadmaps, and those who enjoy balancing statistical depth with practical constraints. Candidates interested in mentoring and raising engineering standards in analytics teams will find a clear fit signal here.
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
Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.
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.
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
