About the role
About
the role You'll be Gamma's first Data Scientist, turning massive volumes of user data and AI outputs into insights that shape how millions of people create content. With over 1 million AI-generated presentations and 5 million AI images created daily, the signal is enormous. Your job is to find the patterns, measure what matters, and help us ship better features faster. You'll design A/B tests that measure product impact, build frameworks that reveal how our AI models perform across user segments, and investigate the hard questions: what makes a good AI-generated presentation, and why does a feature land differently for enterprise versus consumer users? You'll partner closely with product, engineering, and design to define quality metrics, uncover edge cases, and guide decisions with data. This is an IC role for someone eager to be hands-on, but it can grow into a leadership position establishing the Data function at Gamma. You'll thrive here if you're curious, comfortable with ambiguity, and excited to figure out what questions to ask rather than just answering the ones given to you. Our team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.
What you'll do Build frameworks that help
the team understand AI model performance, user behavior, and product health across Gamma's platform Dig into AI model outputs across user cohorts to identify quality gaps and create evals and metrics to measure improvement Partner with engineering and product to define quality metrics for AI-generated content and user satisfaction Develop statistical models and frameworks that empower product teams to make data-informed decisions independently Design and analyze large-scale A/B tests and experiments with statistical rigor to measure product impact and guide prioritization What you'll bring 8+ years of experience as a data scientist at product-focused tech companies, with experience managing or mentoring other data scientists Strong statistical foundations with hands-on experience designing and analyzing A/B tests and experiments at scale Experience working with large-scale data and building metrics frameworks from scratch, including modern data stack tools like dbt and Snowflake and comfort analyzing unstructured or text data Experience working with AI/ML products, especially LLMs or generative AI, with familiarity evaluating model performance in production settings Ability to communicate complex technical concepts to non-technical stakeholders and influence product decisions with clarity and conviction A clear perspective on how agentic coding is transforming the data science role, and genuine excitement about applying AI to your own work (
