Senior or Staff Data Scientist, Suno
Recommendations
$200-300k
+ Company Equity Package
More information about location
AI music generation tools
Open for applications
AI music generation tools
101-200 employees
Open for applications
$200-300k
+ Company Equity Package
More information about location
101-200 employees
Company mission
To build a future where anyone can make music.
Role
Who you are
- 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
- 6+ years experience in data science or machine learning roles with direct experience on recommendation systems - ideally in consumer products, music/audio, or content platforms
- Strong technical skills in Python, SQL, and statistical modeling
- 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
What the job involves
- As our founding Recommendation 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
- 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
Our take
Suno is a company leveraging AI for music creation, attempting to make it accessible to everyone, regardless of their musical background. The platform allows users to generate complete songs by inputting text prompts, breaking down the barriers that traditionally separate amateurs from professional musicians.
Unlike other AI music tools, Suno focuses on ease-of-use, enabling even those with no music theory knowledge to produce professional-sounding songs. This approach has already attracted a diverse user base, including everyday people and GRAMMY-winning artists.
Suno' rise has been fast and impressive, but it's now facing serious legal heat, including new lawsuits from independent artists. If it can defend its practices ad show respect for creators' rights, there's still a strong future ahead for the company.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Nov 2025
$250m
SERIES C
May 2024
$125m
SERIES B
Total funding: $375m
Company HQ
Mid-Cambridge, Cambridge, MA
Leadership
Mikey Shulman
(Co-Founder & CEO)Previously worked as Head of Machine Learning at Kensho Technologies. Also worked as a Lecturer for the MIT Sloan School of Management.
Georg Kucsko
(Co-Founder & CTO)Also works as a Lecturer at the MIT Sloan School of Management. Prior work includes Head of AI Research at Kensho Technologies.
Martin Camacho
(Co-Founder)Previously worked as Engineering Director at Firefly Health and Chief Architect and Board Director at Kensho Technologies.
Keenan Freyberg
(Co-Founder & COO)Worked in Business Devlopment at Pinshape, and as an Associate at Capco. Also worked through several roles at Kensho Technologies.
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