PhD Intern, Data Science (2027)
Figma is hiring a PhD Intern, Data Science (2027) in San Francisco and New York, United States. Level rates it ; you can apply on Figma.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Python, PyTorch and TensorFlow.
- Level classifies it as an internship.
- Level lists 144 other open roles at Figma.
AI in this role
PhD intern to conduct data science research, apply machine learning and experimentation, and influence AI product features at Figma.
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!
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.
What you’ll do at Figma:
- 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
We’d love to hear from you if you have:
- 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
While it's not required, it's an added plus if you also have:
- 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
At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Pay Transparency Disclosure
This internship role is based in either Figma’s San Francisco or New York hub offices, and has the hourly base pay rate stated below. Figma also offers interns a housing stipend and travel reimbursement. Figma’s compensation and benefits are subject to change and may be modified in the future.
Internship$68—$68 USDAt Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
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.
By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice.
Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles:
- Candidates may submit up to 5 applications during any rolling 30-day period.
- Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection.
Once the applicable days has passed, candidates are welcome to apply again.
How we rate this
PhD Intern, Data Science (2027) at Figma rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where statistical modeling was part of your work. What did you do?
- Tell me about a project where causal inference was part of your work. What did you do?
- Tell me about a project where experimentation was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine learning, Statistical Modeling, Causal Inference, Experimentation, and Data Science. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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