Research Data Scientist, Cloud Demand Forecasting and Capacity Planning

Google’s Cloud Capacity Data Science (CCDS) team is building scalable data science solutions that help improve how Google Cloud forecasts demand and plans capacity. In this onsite role in Thornton, CO, you’ll develop forecasting models and capacity planning solutions designed to support Cloud’s business objectives and help deliver a strong obtainability experience for customers. You’ll also contribute to advanced machine-learning approaches for forecasting organic and inorganic demand across multiple Cloud products, while using operations research methods to recommend actions based on future demand.

Compensation: $147,000 - $210,000 (USD) per year + 15% bonus target + equity + benefits.

What you’ll do

• Develop, maintain, and improve forecasting models and capacity planning solutions to support Cloud’s goals.
• Enable efficient use of Cloud infrastructure while working toward service level objectives for Cloud customers.
• Drive end-to-end technical work as an individual contributor, making larger, mostly independent contributions toward a larger team goal with minimal assistance.
• Create the methodologies needed to address ambiguous problem spaces, owning solutions that extend beyond analysis, including supporting launches, cross-functional collaboration, and documentation.
• Partner with engineers and subject matter experts, integrating with a cross-disciplinary team and demonstrating working knowledge across data science and related technical areas.
• Deploy and contribute to advanced machine-learning models that forecast organic and inorganic demand for many Cloud products.
• Use operations research methods to develop algorithms that recommend actions based on forecasts of future demand.
• Collaborate with a multi-disciplinary group, including engineers, program managers, and product managers, to optimize a fast-growing fleet at massive scale and flexible configuration.

Requirements

• Master’s degree in a quantitative field such as Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related discipline.
• 3+ years of work experience using analytics to solve product or business problems, including coding (e.g., Python, R, SQL) and querying databases or conducting statistical analysis, or a PhD.

Preferred qualifications

• PhD in Operations Research, Industrial Engineering, Statistics, or a related field.
• 5+ years of analytics experience solving product or business problems, including coding (Python, R, SQL), querying databases, or statistical analysis, or a PhD.
• 4+ years of relevant experience (e.g., as a data scientist), including advanced analytics applied to planning and infrastructure problems.
• Experience designing and building statistical forecasting models.
• Experience designing and building machine learning models.
• Excellent problem framing, problem-solving, and project management skills.

Location

• Thornton, CO (onsite)
• Atlanta, GA, USA

Tech stack: Python, R, SQL.