AI Data Scientist
San Francisco, California, United States
- Pay
$180,000–310,000/year · BaseAnnual period assumed · Plus equity — pay source
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.
Read the full posting- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou'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.
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.
Build frameworks that help the team understand AI model performance, user behavior, and product health across Gamma's platform
Partner with engineering and product to define quality metrics for AI-generated content and user satisfaction
From the employer’s posting
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 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.
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
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
Tools in this posting
- dbt
- Snowflake
Source — Tool mentions in context
- 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
Job description
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Source & posting history
Source notes
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- Pay
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.
- Location & working pattern
San Francisco, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 93
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Nov 9, 2025
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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