AI Data Scientist
At a glance
Mid-level AI Research role at Gamma. San Francisco · full-time · $180,000–$310,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Create ways to track AI model results, user activity and product health across Gamma
- Review model outputs by user group, spot quality problems and build evaluations to measure progress
- Set measures for generated-content quality and user satisfaction alongside product and engineering
- Build statistical methods that help product teams make decisions with evidence
- Plan and analyze large-scale A/B tests to gauge product impact and inform priorities
What you bring
- At least eight years working as a data scientist in product-led technology companies, including experience guiding other data scientists
- Strong grounding in statistics and hands-on work planning and assessing large-scale A/B tests
- Experience creating metrics frameworks with large datasets, dbt and Snowflake, and text or other unstructured data
- Background with AI/ML products, especially generative AI, and evaluating model performance in production
Who this fits
This hands-on individual contributor role may later expand into establishing and leading the data function. It suits someone curious, comfortable with ambiguity, and able to explain technical ideas clearly to nontechnical partners. The job is based in San Francisco, with in-person work four to five days each week and some work-from-home flexibility.
From the employer
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 (Nice to have)
Compensation range:
The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K - $310K plus benefits & equity.
Final offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above.
If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.