Data Scientist, Core Data - PhD (2026)

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We're looking for a research-minded Data Scientist to join the Core Data team. This team is a group of analytics professionals and Engineers building the foundational platforms for data science at Figma. We build the experimentation, analytics, and AI tooling that every product team relies on to make confident, data-driven decisions, partnering closely with Data Infra, ML, and Applied Science to evolve our platforms and embed AI into the daily workflows of data scientists across the company. This role is for someone who thrives at the intersection of rigorous research and real-world impact. You'll bring PhD-level depth to problems that matter. This includes advancing our experimentation platform and developing machine learning-based analytical systems. You will also help craft how we measure AI-powered features through causal inference and statistical modeling. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: · Partner across teams to define and track important metrics, develop experiments, and uncover insights that inform strategic decisions · Accelerate Figma's experimentation platform and methodology, including A/B testing frameworks and causal inference techniques · Construct models and analytical frameworks based on machine learning to support product, platform, and business initiatives · Create tools, datasets, and systems that enable others to work with data more efficiently and rigorously · Complete and own complex data projects end-to-end, from problem prioritisation to solution delivery · Drive data quality, accessibility, and the democratization of data across the organization We’d love to hear from you if you have: · PhD in a quantitative field (Statistics, Computer Science, Economics, Operations Research, Physics, or related) with a strong foundation in statistical methods, experimentation, and/or machine learning · Fluency in SQL and proficiency in a scripting language like Python or R, with exposure to distributed data systems (e.g. Snowflake) through research or internships · Ability to communicate technical concepts clearly to both technical and non-technical audiences · A curious and rigorous mindset, with a passion for translating research into real-world impact While it’s not required, it’s an added plus if you also have: · Publications or research experience in experimentation or applied ML; industry internship experience applying data science to product or business problems · An AI-native mindset, with exposure to or interest in LLM analytics, AI product measurement, or evaluating the impact of AI-powered features · A self-starter attitude and the ability to thrive in ambiguous and fast-paced environments Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. $170,000—$178,000 USD Examples of accommodations include but are not limited to: · Holding interviews in an accessible location · Enabling closed captioning on video conferencing · Ensuring all written communication be compatible with screen readers · Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.