Job Description

About Suno At Suno, we are building a future where anyone can make music. You can make a song for any moment with just a few short words. Award-winning artists use Suno, but our core user base consists of everyday people making music — often for the first time. We are a team of musicians and AI experts, including alumni from Spotify, TikTok, Meta and Kensho. We like to ship code, make music and drink coffee. Our company culture celebrates music and experimenting with sound — from lunchroom conversations to the studio in our office. About The Role As our founding Recommendation Algorithms Data Scientist, you'll be instrumental in building Suno's music discovery and recommendation systems from the ground up. You'll help define how millions of users discover, create, and engage with music on our platform. This role combines technical expertise in recommendation systems with the creative challenge of applying strong principles and judgment to determine what truly compelling and valuable music recommendations look like. You'll work at the intersection of music, AI, and human behavior, collaborating closely with engineering, product, and growth teams to build systems that help users find their next favorite song or inspire their next creation. From hands-on data exploration and rapid prototyping to building up sophisticated ML models, you'll be deeply involved in the full spectrum of recommendation strategy and execution. This role is perfect for someone who thrives in open-ended environments, loves getting their hands dirty with data and prototyping, and is excited about defining the future of music discovery. Check out the Suno version of the job here! What You’ll Do Define content strategy: Partner with product and growth leaders to establish our initial content discovery strategy, recommendation goals, and success metrics Get hands-on: Dive deep into user behavior patterns and content characteristics, using these insights to prototype and improve upon recommendation algorithms and features Design and run experiments: Create rigorous testing frameworks to validate recommendation improvements and measure impact on user engagement, retention, and music creation Build evaluation systems: Develop comprehensive frameworks for measuring recommendation quality across multiple dimensions - relevance, diversity, novelty, and user satisfaction Collaborate cross-functionally: Work closely with engineering to test and implement recommendation algorithms and with product to shape user experience Shape data culture: As a part of our growing data science team, contribute to strong data foundations and foster a nuanced and healthy company-wide relationship with data What You’ll Need 5+ years experience in data science or machine learning roles with direct experience building recommendation systems - ideally in consumer products, music/audio, or content platforms Strong technical skills in Python, SQL, and modern ML techniques for recommendations Experience designing and running rigorous experiments, evaluating tradeoffs, deriving clear insights, and making actionable recommendations Excellent communication and experience working across multiple functions to influence decisions A self-starter mentality with the ability to thrive in ambiguity, eagerness to wear multiple hats, and passion for continuous learning Additional Notes: Applicants must be eligible to work in the US. This is an onsite role in Cambridge, NYC, Venice Beach, or SF Benefits Healthcare for you and your dependents, with vision and dental 401k with match Generous commuter benefit Flexible PTO Compensation Range: $170K - $230K #J-18808-Ljbffr 卵湯

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