data
Posted Apr 23Data Scientist, Core Data - PhD (2026)
at Figma
New York, United StatesOn-site
Responsibilities
- 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
Requirements
- 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.
- 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.
- 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.
- 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
- 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