Lead Data Scientist (Safety)

About this role

WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well.

We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

ABOUT THE ROLE As a Lead Data Scientist at Faculty, you will drive the scientific direction and architectural rigour of upstream AI safety and evaluation standards. Partnering directly with Frontier Labs, you will lead the design of novel experiment frameworks, mentor technical teams, and ensure delivery excellence across high-stakes engagements. Bridging deep scientific research with client strategy, you will champion robust methodologies, guide cross-functional teams, and advance Faculty’s thought leadership in practical AI safety.

WHAT YOU'LL BE DOING: - Directing project teams to deliver cutting-edge upstream AI safety solutions and evaluation standards to Frontier Labs - Architecting core scientific experiment designs and robust software infrastructure for high-impact safety engagements - Guiding and mentoring data scientists, nurturing technical capabilities, and fostering an inclusive, high-performing team culture - Partnering with commercial leads and executive stakeholders to scope technical work, assess feasibility, and translate complex challenges into rigorous scientific frameworks - Advancing Faculty’s industry leadership by innovating novel evaluation methodologies, speaking at key forums, or publishing open-source research - Establishing and upholding scientific methodology, rigour, and engineering best practices across the full project lifecycle WHO WE'RE LOOKING FOR: - You bring extensive leadership experience in quantitative data science, upstream AI safety research, or academic research with exemplary experiment design methodology.