Sr. Data Scientist, Responsible AI

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale Generative AI experiences — including Pinterest Assistant and Canvas — ensuring these products are safe, fair, and trustworthy is paramount. We are looking for a Senior Data Scientist to help lead Pinterest's responsible AI mandate within the Advanced Technology Group (ATG). In this role, you will design and build the data science foundations for automated adversarial testing of our GenAI products — developing attack strategies, evaluation frameworks, and harm-detection methodologies that operate at scale. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Trust & Safety specialists, Policy teams, and Product Managers. You are expected to develop a deep understanding of generative AI vulnerabilities, and generate insights and robust methodologies to proactively surface and mitigate risks. The results of your work will directly influence product safety, policy compliance, and user trust across Pinterest. What you'll do Design and develop automated adversarial testing methodologies — including single-turn, multi-turn, and multimodal attack strategies — to proactively identify vulnerabilities in Pinterest's Generative AI products. Build and calibrate hybrid evaluation pipelines combining LLM-based judges, classifiers, and rule-based systems to accurately detect safety violations, policy breaches, bias, and representational harms. Develop and operationalize harm taxonomies grounded in industry standards and Pinterest's Responsible AI and Trust & Safety threat models. Design adaptive refinement loops that learn from attack outcomes (near-misses, partial failures) to iteratively surface deeper and previously unknown vulnerabilities. Bring scientific rigor and statistical methods to the evaluation of AI safety — including benchmark dataset construction, evaluation calibration, and success-metric definition (vulnerability severity, coverage breadth, pre-launch risk reduction). Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML engineers, Trust & Safety specialists, policy teams, product managers, and legal partners to ensure safe product launches. Relentlessly focus on impact, whether through influencing product safety strategy, advancing responsible AI metrics, or improving critical evaluation processes. Mentor and up-level junior data scientists and cross-functional partners on adversarial evaluation, responsible AI methodologies, and safety-aware data science practices. What we're looking for 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data. Strong interest and hands-on experience in one or more of: AI safety, adversarial machine learning, red teaming, responsible AI, or trust & safety. Deep familiarity with large language models (LLMs), generative AI systems, and their failure modes — including prompt injection, jailbreaks, bias, and safety violations. Experience designing and calibrating evaluation frameworks for AI systems — including LLM-as-judge, classifier-based evaluation, and benchmark dataset construction. Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines and large-scale experimentation. Familiarity with AI safety taxonomies and frameworks (e.g., OWASP LLM Top 10, MITRE ATLAS) is strongly preferred. Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership. Excellent written and verbal communication skills, wi