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San Francisco, California, United States
Onsite
We're building the world's first creative entertainment platform, where the entire world can feel the joy and fulfillment of making music. Music is for everyone: Our users include everyone from grandmothers creating songs for their loved ones, to Grammy winners using Suno Studio, our power tool, to make the most popular hits in the world.
Building the future of entertainment requires ambition. The pace is fast, the problems are hard, and the work demands ownership and intensity. For the right people, it’s incredibly rewarding: a chance to shape a new medium, work with a small team that cares deeply about quality, make music, drink too much coffee, and build something that millions of people use to express themselves in ways that were never before possible.
Suno is the fastest growing consumer entertainment company and the leader in AI music. We are backed by leading investors including Bond Capital, Menlo Ventures, Lightspeed Venture Partners, IVP, Forerunner, Union Square Ventures, Alkeon, Quiet, Matrix Partners, Schroders Capital and, NVentures (venture arm of NVIDIA).
Trust should be the foundation of every relationship Suno has — with our users, our artists, our rightsholders, and the broader music community. We're looking for our first dedicated data scientist on the Trust & Safety team to help make that real by building the metrics and analysis that let us measure how we're doing, and collaborating to define and execute on an impactful roadmap. You'll partner closely with product, engineering, and legal to bring a rigorous, quantitative lens to problems like copyright detection, content filtering, and bot detection. You and cross-functional stakeholders will work together to create a seamless creative environment for our users that is built on security and trust.
Define and evaluate metrics for the health of our trust and safety ecosystem
Analyze and build models, algorithms, and methodologies for maintaining a safe platform, like bot detection, content filtering, copyright detection, etc.
Design and run experiments that measure the real impact of changes to Trust & Safety practices, and turn results into clear recommendations
Partner with product and engineering to size opportunities and shape the Trust & Safety roadmap
Contribute to building strong data foundations as part of our awesome data science team
6–8 years of experience in data science or a closely related analytical field, with several years in trust & safety or closely adjacent problems (e.g., spam/fraud, integrity, policy-adjacent ML)
Strong hands-on SQL and Python
Experience running online experiments end-to-end, from ideation and metrics selection through analysis and informing the final decision
Experience building metrics or evaluation frameworks from scratch, without established precedent to lean on
Experience training and building predictive ML models, offline and real-time.
Musician or creative hobbyist
This role is expected to work from the designated Suno office 5 days a week, per Suno's company policy. Full-time employees will receive competitive equity packages, and comprehensive benefits. The actual base salary offered may vary depending on location, skills, qualifications, and experience.
Applicants must be eligible to work in the US.
Company Equity Package
401(k) with 3% Employer Match & Roth 401(k)
Medical, Dental, & Vision Insurance (PPO w/ HSA & FSA options)
11 Paid Holidays + Unlimited PTO & Sick Time
16 Weeks of Paid Parental Leave
Creative Education Stipend
Generous Commuter Allowance
In-Office Lunch (5 days per week)
Suno is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the Massachusetts Fair Chance in Employment Act, NYC Fair Chance Act, LA City Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.
