PhD Intern, Data Science (2027)

Figma•San Francisco, CA

13h•Onsite

About The Position

Figma is growing its 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! Figma’s Data Science team partners across product, engineering, design, marketing, sales, and operations to help Figma make better decisions with data. As a PhD Data Science Intern, you’ll bring rigorous research training to some of Figma’s most important and open-ended questions, from researching emerging product and user behaviors and Figma’s broader ecosystem to developing new measurement methodologies, applying causal inference or machine learning, and building analytical systems. You’ll own a data science project end-to-end: from framing the question and methodology to translating findings into insights that influence Figma’s products, strategy, or data science practices; with the potential to continue toward publication after the internship. This internship will be based out of our San Francisco or New York hub.

Requirements

Currently pursuing a PhD in Data Science, Statistics, Computer Science, Human-Computer Interaction (HCI), Economics, Operations Research, Physics, Applied Mathematics, or a related quantitative field; with demonstrated experience conducting independent research (e.g. thesis or equivalent research milestone)
Demonstrated fluency in one or more research methodologies or technical areas, such as statistics, experimentation, machine learning, causal inference, econometrics, optimization, user research methods, or AI/LLMs
Experience using a scripting language such as Python or R, as well as proficiency with SQL, for analysis, modeling, or work with complex or large-scale datasets through research, internships, or applied projects
Ability to explain technical concepts clearly and connect analysis to decisions, recommendations, or product/business impact
A curious, rigorous, and self-starting mindset, with the ability to thrive in ambiguous, fast-moving environments and translate research into real-world impact

Nice To Haves

Prior industry or applied research experience with experimental design, causal inference, forecasting, product measurement, user research, or applied machine learning to influence product, business, platform, or stakeholder decisions
Publications or research relevant to applied data science
Experience or interest in AI product measurement, LLM analytics/evaluation, recommendation systems, search, personalization, or evaluating AI-powered features

Responsibilities

Partner with cross-functional teams to turn ambiguous product, platform, or business questions into well-defined data science problems
Analyze user, product, or business data to uncover insights and recommend actions
Design and evaluate experiments, metrics, statistical or machine learning models, and analytical frameworks
Communicate assumptions, tradeoffs, limitations, and recommendations clearly to technical and non-technical partners
Own a focused internship project end-to-end, from problem framing and technical execution through final recommendations, with potential to continue toward publication after the internship