[Hiring] Applied Data Researcher @Figma

Role Description

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.

We're looking for an Applied Data Researcher who combines scientific depth with a proactive builder mindset. Reporting directly to our Head of Data, with regular visibility with C-level executives, you'll identify and vet opportunities, lead investigations into critical questions, and build useful Data products, tools, and prototypes. You'll work across Data Science, Engineering, Product, Design, and AI Research, building directly and providing technical direction to teams of other scientists as efforts grow.

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:

• Identify and vet consequential opportunities across Data products and tools, AI measurement and evaluation, and applied data capabilities; lead investigations and shape priorities with partners.
• Develop and validate methods for evaluating generative AI and agentic workflows, including representative datasets, baselines, rubrics, and evals; investigate uncertainty, bias, failure modes, and real user outcomes.
• Personally write code and build or adapt LLM-powered tools, agentic workflows, models, prototypes, and demos that test scientific, product, and tool hypotheses, using AI-assisted coding and analysis in your work.
• Provide technical direction and oversight for larger projects, delegate work to teams of senior and staff scientists, and mentor scientists and engineers while maintaining a substantial personal contribution to code and methods.
• Independently drive delivery or partner with engineering to turn useful prototypes into maintained systems, balancing quality, latency, cost, reliability, and iteration speed.
• Establish reusable methods, tools, and technical standards; iterate with users, drive adoption across teams, and use evidence to improve an approach or recommend a change in direction.
• Communicate findings, recommendations, limitations, and tradeoffs clearly to partners and C-level executives, connecting scientific and technical work to important product and company decisions.

Qualifications

• Deep expertise in machine learning, statistics, causal inference, or a related quantitative field, plus hands-on experience in generative AI evaluation and measurement, including evals, labeling, and agentic workflows.
• Fluent programming skills in Python or a comparable language, plus SQL, and a record of independently building, debugging, testing, and reviewing useful software, including working effectively with AI-assisted development tools.
• A proactive builder mindset and end-to-end ownership: experience identifying important opportunities and carrying ambiguous work through method development, implementation, rigorous evaluation, and sustained use by others.
• A sustained record of company-, organization-, or cross-pillar scientific impact, including shaping technical direction, overseeing larger projects, and leading other senior scientists through influence and delegation.
• Strong judgment, independence, and collaborative communication, including experience making recommendations to C-level executives, explaining uncertainty and tradeoffs, and aligning partners on priorities and decisions.

Requirements

• While it's not required, it's an added plus if you also have:
• Experience with human labeling, automated judge validation, conversational data, or multimodal AI and machine learning.
• Experience building interactive applications, lightweight interfaces, APIs, or reusable open-source tools.
• Cloud and data infrastructure experience; familiarity with Snowflake, AWS, Dagster, dbt, or Hex is useful, but no particular vendor or framework is required.
• An MS or PhD in machine learning, computer science, statistics, or a similar quantitative discipline; graduate research, publications, or equivalent applied depth.

Benefits

• Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage.
• Retirement benefits with company contributions.
• Parental leave and reproductive or family planning support.
• Mental health and wellness benefits.
• Paid time off, including paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws.
• Exempt employees are eligible for employer-provided paid flexible PTO in addition to flexible paid sick leave, subject to manager approval.
• Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts.
• Sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles.