• 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. 

Qualification Required

• 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.

Qualification Required :

• 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.

• Own key areas of the Snowpark platform and prioritize, plan, and innovate to drive business results.
• Participate and present in regular business and product reviews to cross-company leadership and executives.
• Work in a cross-functional and collaborative role spanning product, design, development, documentation, QA, marketing, sales, and support as well as our business partners.
• Collaborate across the Snowflake leadership team as well as the PM and Engineering.
• Lead customer programs and engage in frequent conversations with customers to understand their needs, listen to their feedback, and determine the usability of the product which will influence the product roadmap and feature design.
• Partner with other Snowflake Product Managers on cross-company initiatives.
• Help coordinate project execution across feature teams.
• Leverage data to help find the best solution to our complex problems.

Qualification Required

• An understanding of Snowflake’s Data Cloud vision, and how Snowpark fits into the larger picture.
• Prior experience as a product manager – identifying customer needs, prioritizing and delivering features, and measuring impact.
• Proven expertise in understanding the voice of the customer and partnering across engineering, marketing, and sales to deliver compelling products that meet those customers’ needs.
• Experience with cloud offerings and distributed compute or data workloads.
• Decisive and detailed oriented personality, and ready and willing to stand by their decisions.
• Ability to thrive in the dynamic environment that comes with being part of a hyper-growth company. That means flexibility and willingness to jump in and do whatever it takes to be successful.
• Crisp and clear communicator who is able to align individuals at various technical levels.
• Ability to work with teams in multiple geographies.
• 2+ years of experience in product management.
• Prior experience working with data processing, data pipeline, or cloud compute technologies is considered a plus.
• Prior experience working with database systems is considered a plus.
• Bachelor’s degree in Computer Science, Engineering or similar.

• Prepare quarterly earnings materials, including investor presentation and Q&A.   
• Draft investor communications for industry conferences. 
• Maintain relationships with external stakeholders. Respond to IR email inquiries.  
• Support relationships with equity research coverage.  Monitor research notes and financial models.
• Research industry trends, competitive landscape, and internal product development efforts. 

QUALIFICATIONS :

• 4+ years of experience in equity research, investor relations, or corporate FP&A
• Experience with public software companies
• Bachelor’s degree in Finance, Accounting, Economics, or other relevant field
• Strong written and verbal communication skills
• Attention to detail