Data Scientist, Marketing
First Data Scientist supporting Brand Marketing at Figma. Build measurement frameworks, attribution models, and ML solutions to evaluate brand investments and drive marketing strategy.
What you'll do at Figma
- Develop and own end-to-end measurement frameworks, attribution models, and channel-level evaluation tools to assess the impact of Figma's marketing investments across the full funnel and inform budget allocation
- Partner with stakeholders across Brand Marketing, Email, Lifecycle, Demand Gen and Research teams to define success metrics, uncover insights, and drive data-informed decision making
- Develop and apply statistical and machine learning models to solve key marketing challenges, including audience targeting, creative effectiveness, customer engagement, and campaign performance measurement
- Build dashboards, reporting frameworks, and analytical tools that help stakeholders understand brand performance and business impact
- Translate complex analyses into clear recommendations for marketing leaders and executive stakeholders
- Improve data quality, measurement infrastructure, and reporting capabilities to support a growing marketing organization — establishing standards and processes that scale with the business
- Proactively surface new opportunities to improve marketing effectiveness — from audience targeting to spend optimization — and bring data-backed recommendations to senior marketing and business planning discussions
Requirements
- 5+ years of experience in Data Science or Marketing Analytics, with a track record of supporting Marketing teams and measuring the impact of large-scale brand investments
- Strong foundation in statistics, experimentation, causal inference, and working with survey or qualitative research data
- Advanced proficiency in SQL and experience using Python, R, or similar tools to conduct analysis and build scalable measurement solutions
- Proven ability to influence senior non-technical leaders and cross-functional teams by translating complex analyses into clear, actionable recommendations
Nice-to-haves
- Experience with media mix modeling (MMM) or multi-touch attribution (MTA) methodologies
- Hands-on experience with marketing data platforms such as Segment, Amplitude, or similar tools
- Experience working in a B2B SaaS or PLG environment
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