Google

Runs Search and YouTube and builds Gemini AI

Staff Research Data Scientist

AI ResearchConfirmed live in the last 24 hours

Full-time

About the Job

Requirements

A Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field is required.
At least 8 years of experience using analytics to solve product or business problems, coding in languages such as Python, R, or SQL, and querying databases or performing statistical analysis.
Experience conducting machine learning research and developing new methodologies or algorithms.
Experience with large language models, natural language processing, or generative AI.
Experience with machine learning algorithms and statistical modeling.
Experience with cyber threat research.

Responsibilities

Define and drive the multi-quarter research strategy and technical roadmap at the intersection of machine learning for security, AI-powered security operations, and autonomous threat investigation and response.
Serve as the Technical Lead for applied research workstreams, translating ambiguous threat challenges into structured AI/ML modeling solutions with product impact.
Architect state-of-the-art model architectures and agentic systems, balancing theoretical novelty with low-latency, resilient inference in adversarial environments.
Architect end-to-end data acquisition and curation strategies across heterogeneous security telemetry, and establish benchmarks and evaluation pipelines for robust model assessment.
Partner with Engineering and Product Management leadership to establish shared architectural roadmaps, govern production machine learning deployments, and lead post-deployment telemetry and feedback loops.
Define technical goals, drive applied research agendas, and lead the technical execution of machine learning, deep learning, and generative AI initiatives across cybersecurity product areas.
Drive research and technical execution across agentic security operations, threat intelligence reasoning and contextualization, security-specialized large language models and foundation models, and dark web threat detection.
Bridge AI research and enterprise-grade deployment by architecting research prototypes, steering data strategy, aligning roadmaps with cross-functional engineering and product leaders, and mentoring junior researchers.
Represent security research externally through publications, patents, and conference presentations.

Desired Qualifications

A PhD in Computer Science, Data Science, Statistics, Electrical Engineering, or a related quantitative field.
At least 7 years of experience designing, validating, and deploying machine learning models, statistical methods, or generative AI systems into production.
At least 2 years of applied experience in cybersecurity, security operations, threat intelligence, fraud or abuse, or vulnerability research.
Experience acting as a Technical Lead, workstream owner, or principal researcher directing technical projects end-to-end across cross-functional teams.
Experience addressing distribution shifts, concept drift, or adversarial attacks in high-stakes or non-stationary environments.
Experience in production-grade development using programming languages and modern deep learning ecosystems.

Define and drive the multi-quarter research strategy and technical roadmap at the nexus of machine learning for security, AI-powered security operations, and autonomous threat investigation and response.
Serve as the Technical Lead (TL) for applied research workstreams, translating ambiguous threat challenges into structured, high-impact AI/ML modeling solutions with landed product impact.
Architect state-of-the-art model architectures and agentic systems, balancing theoretical novelty with low-latency, resilient inference in adversarial environments.
Architect end-to-end data acquisition and curation strategies across massive, heterogeneous security telemetry; establish benchmarks and evaluation pipelines for robust model assessment.
Partner with Engineering (SWE) and Product Management (PM) leadership to establish shared architectural roadmaps, govern production ML deployments, and lead continuous post-deployment telemetry and feedback loops.

Minimum qualifications:

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience with Machine Learning research and developing new methodologies or algorithms.
Experience with Large Language Models (LLMs), Natural Language Processing (NLP), or Generative AI.
Experience with Machine Learning algorithms and statistical modeling.
Experience with cyber threat research.

Preferred qualifications:

PhD in Computer Science, Data Science, Statistics, Electrical Engineering, or a related quantitative field.
7 years of experience designing, validating, and deploying machine learning models, statistical methods, or generative AI systems into production.
2 years of applied experience within cybersecurity, security operations, threat intelligence, fraud/abuse, or vulnerability research.
Experience acting as a Technical Lead, workstream owner, or principal researcher directing technical projects end-to-end across cross-functional teams.
Experience addressing distribution shifts, concept drift, or adversarial attacks in high-stakes or non-stationary environments.
Experience in production-grade development using programming languages and modern deep learning ecosystems.

The Google Cloud GUSTO AI Data Science Research team develops innovative, data-driven solutions to today’s most challenging cybersecurity problems. By leveraging data derived from Google's unparalleled view of the threat landscape, our cross-functional, applied research team experiments and delivers impactful findings for both our customers and the broader cybersecurity industry.

As a Staff Research Data Scientist (Tech Lead) you will define the technical goal, drive applied research agendas, and lead the technical execution of machine learning, deep learning, and generative AI initiatives across Google SecOps, Google Threat Intelligence, and other key cybersecurity product areas in Google Cloud.

In this role, you will manage high-ambiguity, adversarial security problems at Google scale. You will act as the principal research driver and technical lead across initiatives such as agentic security operations, threat intelligence reasoning and contextualization, security-specialized LLMs/foundation models, and dark web threat detection. As a Tech Lead, you will bridge the gap between breakthrough AI research and enterprise-grade deployment: architecting novel research prototypes, steering data strategy, aligning roadmaps with cross-functional SWE and Product leaders, and mentoring junior researchers. You will represent Google's security research externally through high-impact publications, patents, and conference presentations, shaping how the broader AI Security industry defends against advanced threat actors.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Sunnyvale, CA, USA.

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience with Machine Learning research and developing new methodologies or algorithms.
Experience with Large Language Models (LLMs), Natural Language Processing (NLP), or Generative AI.
Experience with Machine Learning algorithms and statistical modeling.
Experience with cyber threat research.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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