We’re looking for a Senior Data Scientist to join Snowflake's Security Data Science team. In this role you will partner with Product Security & Security Engineering teams for detecting threats to Snowflake’s Cloud Infrastructure and the Snowflake platform. 

We expect you to support our team culture by working in the office 3 days a week (Tuesday, Wednesday, Thursday). To ensure working in the office, there is an expectation to live within a reasonable commuting distance to office you will be working in. Subject to change.

AS A SENIOR DATA SCIENTIST, YOU WILL :

• Work closely with stakeholders to understand the use-cases and identify focus areas with the highest potential for impact
• Define and analyze metrics that will in-turn inform the key drivers for decision making & operational efficiencies
• Analyze large amounts of messy data, work on data quality, uncover actionable insights and present them in a compelling manner
• Provide technical & thought leadership designing and implementing machine learning techniques

OUR IDEAL CANDIDATE WILL HAVE :

• High levels of curiosity and eager enthusiasm for open-ended problems
• Experience and interest in problem formulation based on relatively abstract information 
• Deep understanding of the basic classes of ML algorithms and their underlying assumptions
• 3+ years experience successfully applying supervised and unsupervised machine learning methods on large-scale datasets
• Be able to design and build the security components in a cloud native environment -- previous exposure to AWS, Azure or GCP is necessary.
• Technical expertise in one or more of the following topics: Anomaly Detection, Clustering, Time-Series Analysis, Complex Event Processing, Sequence Mining, Risk Quantification
• 3+ years experience writing production-quality, scalable code using Python 
• Expert level knowledge working with libraries such as scikit-learn, pandas, etc., SQL and Airflow
• Ability to articulate results and complex concepts to leadership
• Preferably, familiarity in working with containers and related cloud technologies is preferred, such as Docker, K8s, or one of EKS, AKS, and GKE.
• Prior experience with DevSecOps