Data Scientist Research, Cloud Security

About the position

The Google Cloud Security Data Science Research team develops innovative, data-driven solutions to today's most challenging cybersecurity problems. By leveraging data derived from Google, Mandiant, VirusTotal's unparalleled view of the threat landscape, the team provides solutions with significant impact for our customers and the broader cybersecurity industry. As a Data Scientist, you will help us solve challenging cybersecurity problems and protect billions of customers by applying your expert knowledge of machine learning and statistics. You will use your previous experience in applying machine learning and statistical techniques to cybersecurity problems, building models and analytic products that have been deployed to customers, and work with massive datasets. In this role, you will partner with Google and Mandiant subject matter experts on the front lines defending against advanced threat actors, iteratively develop new capabilities, and work closely with our Engineering team to deploy and maintain them. Our team handles a wide range of cybersecurity challenges from threat intelligence scoring to dark web threat detection to automated security operations with generative AI. We encourage sharing impactful learnings through publications at academic conferences and talks at industry venues.

Responsibilities

• Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
• Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Requirements

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
• Experience developing in Python.

Nice-to-haves

• 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
• 3 years of experience developing and deploying machine learning and AI models in production settings.
• Experience applying a variety of unsupervised, semi-supervised, and supervised machine learning techniques, and the ability to turn big data into actionable intelligence.

Benefits

• The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits.
• Salary ranges are determined by role, level, and location.
• Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.