Data Scientist, Recommendations and Personalization
California
Cantina
A new social platform where you can create, share, and interact with Al bots live with friends.A bit about Cantina
Cantina, founded by Sean Parker, is a new social platform with the most advanced AI character creator. We enable users to build, share, and interact with AI bots and friends directly in Cantina or across the internet.
Our bots are lifelike, social creatures capable of interacting wherever humans go online. Users can recreate themselves using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots represent a new media type that offers creators a way to share infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.
A bit about the role:
We're looking for a founding Data Scientist to lead personalization and recommendation on Feed and other parts of the Cantina app. You will shape how we use data to power recommendations, user-bot interaction, and social experiences at scale. You’ll be working directly with key product and executive stakeholders, including Sean Parker, to turn data into product-shaping insights and models.
You’ll own the full lifecycle—from data pipelining to modeling to dashboards—to deliver insights that guide strategy and build ML systems that move metrics.
A bit about the work:
Experience building personalization for feed ranking systems
Design, train, and deploy lightweight ML models (e.g. regression, recommendation, neural nets) for real-time applications
Partner with product and engineering to define and run user experiments and A/B tests
Build the foundation of user growth from feed, delivering insights to drive engagement and retention
Build pipelines and foundational metrics for user engagement, retention, and content performance
Build/integrate tools to explain and debug ML models
A bit about you:
5+ years experience in data science, preferably in consumer tech or social platforms
Exceptional SQL skills with demonstrated ability to work with complex data structures
Skilled in Python and standard data science/ML tools (e.g. Pandas, scikit-learn, PyTorch)
Experience building and productionizing models for personalization, recommendation, or ranking
Strong understanding of experimentation and A/B testing
Confident building dashboards for executives and visualizing impact clearly
Comfortable owning end-to-end analytics: from data modeling to insight to delivery
Self-directed, with a bias for action—you can go from zero to insight/model
Bonus: experience with user behavior modeling, fraud/risk analytics, or social content systems
A Bit About the Stack & Tools
Python, SQL
PyTorch for ML Model Prototyping
AWS or GCP for infrastructure
Experimentation framework
Real-time pipelines and feature engineering
Location:
This is a hybrid role, preferably based in the San Francisco Bay Area.
Benefits Summary:
Health Care — 99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.
Monthly Wellness Stipend — $500/month to use on whatever you’d like!
Rest and Recharge — 15 PTO days per year, 10 sick days, all Federal holidays, and 2 floating holidays.
401(K) — Eligible to participate on day one of employment.
Parental Leave & Fertility Support
Competitive Salary & Equity
Lunch and snacks provided for in-office employees.
WFH equipment provided for full-time hybrid/remote employees.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing AWS Engineering Feature engineering GCP Machine Learning ML models Pandas Pipelines Prototyping Python PyTorch Scikit-learn SQL Testing
Perks/benefits: Competitive pay Equity / stock options Fertility benefits Gear Health care Home office stipend Medical leave Parental leave Salary bonus Wellness
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