Build the future of data. Join the Snowflake team.

We’re growing and looking for a talented Senior Data Scientist to come aboard and join our Data Science team in Finance. Our team develops, operationalizes, and maintains the ML-based forecasting models for some of Snowflake’s core financial metrics. Our work product informs many facets of corporate planning and is heavily used by teams inside and outside of Finance, as well as by executive management, the board, and in external reporting to our investors. Our team also works closely with Product to assess the financial impacts of new product features, with Sales to understand and predict customer behavior, and develops and applies anomaly detection algorithms to cost and revenue data.

We are looking for someone who has significant experience employing ML algorithms on time series data and is both equally at home conducting applied research as well as implementing and operationalizing their ideas to meet business driven timelines. As Finance touches on all aspects of the business, you should have a desire to learn about customer behavior and the important drivers of various departments.

• Work with time-series datasets to refine and extend the core forecasting models and algorithms we use for many of our key financial metrics
• Develop and refine ML models that are critical to Snowflake’s business
• Identify and build solutions for operational use cases in forecasting —e.g. further automation, system monitoring and alerting, outlier detection, etc.
• Generate insights into drivers of our business leveraging statistical methods and participate in extending and developing internal tools used for this purpose
• Think creatively to find optimal solutions to our complex, typically unstructured problems.

OUR PREFERRED CANDIDATE WILL HAVE :

• MS/PhD in a quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS)
• Extensive experience building production-ready ML models for time series applications
• Experience conducting open-ended research projects and literature reviews
• 5-7+ years of experience with Python and familiarity with SQL
• Experience working with large-scale machine-generated data (e.g., log, application, or customer-usage data).
• Hands-on experience with MPP databases, such as Snowflake, Redshift, BigQuery, Vertica, etc.
• Ability to clearly present learnings to business leaders and technical stakeholders.
• The ability to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful.