Senior Data Scientist, Finance
Posted on 7/1/2022
Burlingame, CA, USA
Data Structures & Algorithms
- 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 validating ML models for business-critical use cases
- 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
- Work with time-series datasets to refine and extend the core forecasting models and algorithms we use for many of our key financial metrics
- Be the owner of ML models that are critical to Snowflake's business
- Design and operationalize a rigorous continuous improvement framework to ensure our forecasting models remain highly accurate and responsive to business needs
- 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
Data warehouse for the cloud
Snowflake has become a global force to help mobilize the world’s data. Snowflake enables thousands of organizations to have seamless access to explore, share, and unlock the true value of their data.
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