Senior Principal Analyst, Responsible AI Strategy

Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.

The Responsible AI (RAI) pillar within Google Trust and Safety focuses on driving One Google solutions for industry-leading responsible AI applications. It is a global team with Responsible AI domain expertise and different backgrounds in operations, strategy, ethics, risk management, product management, and program management.

Within RAI, the Responsible AI Strategy function fosters coherent strategies and approaches on a range of priority AI issues. We partner with teams across Alphabet and with others across industry to address key AI challenges; we develop and deliver evaluation frameworks; and we help partner teams navigate risks and opportunities related to AI-generated content.

At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.

The US base salary range for this full-time position is $219,000-$305,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Be accountable for cross-cutting clarity, foresight, and strategic alignment for trust and safety issues pertaining to agentic AI products and models.
• Drive projects to address priority agentic AI risks and opportunities, in partnership with a range of functional and product partners.
• Participate in response to escalations and incidents alongside partners across Google and DeepMind. 
  Engage as needed with product and modeling teams to support the above.
• Ensure clear and consistent communications to senior leadership across trust and safety and beyond on key plans and projects.
• Provide partnership and support to other cross-cutting issue areas as needed. This role will work with sensitive content or situations and may be exposed to graphic, controversial, or upsetting topics or content.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 13 years of experience in data analytics, trust and safety, policy, cybersecurity, business strategy, or related fields.

Preferred qualifications:

• Master's degree or PhD in a relevant field.
• Experience in SQL, building dashboards, data collection/transformation, visualization/dashboards, or a scripting/programming language (e.g. Python).
• Experience working with engineering and product teams to create tools, solutions, or automation to improve user safety.
  
• Experience working closely with policy teams.
  
• Education in, or experience with, machine learning.
  
• Excellent communication and presentation skills (written and verbal) and the ability to influence cross-functionally at various levels.