Business Data Scientist, Revenue Acceleration, Google Cloud

Minimum qualifications:

• Master's degree in Engineering, Statistics, a relevant scientific field, or equivalent practical experience.
• 4 years of experience in a Data Science role using data analytics, statistics, mathematics, computer science, or machine learning.
• Experience in any one of the following areas: causal inference, A/B testing, statistical modeling, or Machine Learning.
• Experience with SQL and Python.

Preferred qualifications:

• Experience in publishing research related to Data Science, presenting posters or delivering talks at AI/ML conferences, and contributing to patents.
• Experience in a Data Science role supporting Sales, Marketing, or Customer Support.
• Experience in Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, and R.
• Experience as a Tech Lead.
• Experience drawing conclusions from data, breaking down technical concepts into simple terms, connecting with, and presenting to, technical and non-technical stakeholders, and recommending actions.

About the job

The Revenue Acceleration (Rev-X) team is focused on boosting the growth of Google Cloud with data strategies. They apply AI/ML targeting, accelerate workflows powered by GenAI, and optimize go-to-market strategies with data science. The team is cross-functional, combining Strategy and Operations and Data Science, and working across Sales, Operations, Engineering, Product Management, Marketing and others, to deliver insights and projects that provide sales performance improvements. The team serves many functions in service of growing Google Cloud, including designing business workflows, improving business programs, and developing tools and incentive systems to accelerate business performance.

Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• Process the data from multiple sources and extract insights.
• Research new ways of modeling data for insights and process improvement.
• Perform statistical analyses and build Machine Learning solutions to support Google Cloud business needs.
• Design experiments and use causal inference to measure effectiveness of models, tools, and programs.
• Collaborate on technical work with effective communication to develop quantitative strategies.