Senior Data Scientist, Snowflake

• 5+ years of experience in product data science and/or finance data science roles at a technology company
• Advanced SQL skills, including experience building complex data pipelines and using SQL to perform analysis
• 5-7+ years of experience with Python
• MS/PhD in a quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS)
• 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, high pressure environment. That means being flexible and willing to jump in and do whatever it takes to be successful
• Ability to think creatively to solve problems
• An obsession for detail and quality

Desirable

• We’re looking for a Senior Data Scientist to join our Data Science team in Finance
• This role will work closely with our partners in Product Workload Finance, who play a crucial role in managing the business, financial, and operational performance of our product workloads
• You will provide modeling, analytics, data app development, and data pipelining support as well as work closely with other finance data scientists to align workload forecasting efforts with our top-level corporate forecasts
• Work with a wide range of finance, engineering, and product stakeholders in partnership with the Product Workload Finance team to model and forecast product workloads, define workload financial metrics, and to build tools that enable financial planning under different scenarios
• Partner with Product Workload Finance as well as other finance data scientists to design and perform observational studies and tests to understand the uncertainty of the workload forecasts and devise methods to reduce this uncertainty
• Perform analytics to shed light on key business questions and present on findings
• Research data from key business systems, architect data models and data pipelines, and design end-to-end data apps to support our workload finance team
• 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