AS A SENIOR DATA SCIENTIST AT SNOWFLAKE, YOU WILL :
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.
The following represents the expected range of compensation for this role:
The estimated base salary range for this role is $148,000 - $218,500.
Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.