Build the future of data. Join the Snowflake team.

We are looking for people who have a strong background in data science and cloud architecture to join our Professional Services team and be the technical seller for exciting new offerings and capabilities for our customers! This role will be part of a specialty team in Professional Services that helps our sellers in PS position and scope complex engagements which require deep expertise in specific technology areas.  You will work directly with customers to understand and scope data science use cases using Snowflake's features and its extensive partner ecosystem. The role will also be strategic in determining how to scale technical sales knowledge throughout the Professional Services sales team through packaging of sales plays and delivery of enablement. You will be responsible for understanding Snowflake data science features in order to design high level solutions and proposals based on customer requirements.

AS AN AI/ML PRE-SALES ARCHITECT AT SNOWFLAKE, YOU WILL:

• Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
• Work with Professional Services Practice Directors and Managers on sales pursuits to:
• Understand customer requirements
• Present high level architecture solutions using Snowflake
• Scope and present project plans and effort estimates to deliver AI/ML solutions
• Consult with customers in sales workshops where needed using SQL, Python, Java and/or Scala to understand their Data Science workload / use case.
• Understand best practices related to Snowflake data science capabilities.
• Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them
• Understand our partner system relationships in order to properly position them in the scoping and delivery of AI/ML use cases.
• Provide guidance on how to resolve customer-specific technical challenges.
• Assist in writing Statements of Work
• Identify selling patterns within the AI/ML space, creating go to market options for our PS Sellers to leverage
• Enable PS Sellers with technical knowledge to scale our ability to sell AI/ML solutions
• Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing.

OUR IDEAL AI/ML PRE-SALES ARCHITECT WILL HAVE: 

• Minimum 10 years experience working with customers in a pre-sales or post-sales technical role.
• Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
• Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
• Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models. 
• Experience and understanding of at least one public cloud platform (AWS, Azure or  GCP)
• Experience with at least one Data Science tool such as AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks,
• Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.
• Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar.
• University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience

BONUS POINTS FOR HAVING: 

• Experience with GenerativeAI, LLMs and Vector Databases,
• Experience with Databricks/Apache Spark
• Experience implementing data pipelines using ETL tools
• Experience working in a Data Science role
• Proven success at enterprise software 
• Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential.