Marketing Data Scientist

Suno

active

Official active full-time posting for Marketing Data Scientist at Suno, located in NYC.

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Role facts

Employer	Suno
Location	NYC
Work mode	On-site / not stated
Remote scope	unknown
Employment	full-time
Function	Research & data
Track	industry
Seniority	unspecified
Compensation	140000–200000 USD / year
Posted	2026-05-28
Work authorization	Applicants must be eligible to work in the US.
Official posting	Open official posting ↗

Responsibilities

Suno's marketing team is scaling fast, and we need a Marketing Data Scientist to be the analytical partner driving smarter acquisition decisions. You'll own the data that tells us which channels work, which creatives perform, and where to invest our next dollar.
You'll design and analyze marketing experiments, build attribution models that actually reflect reality, and turn messy data into clear answers. You'll work directly with our performance marketing and creative teams, helping them understand which campaigns are hits and where to invest next.
This isn't a "pull reports and send dashboards" role. You'll be actively shaping how we spend our budget, testing new hypotheses, and solving problems we haven't figured out yet. If you're someone who gets energized by digging into data until it makes sense—and wants to help millions of people discover Suno—this could be a great fit.
Check out the Suno version of this role here: https://suno.com/s/D2ZtlzdFGnWyZKFs
Run marketing experiments – Design and analyze A/B tests and incrementality tests to figure out which channels actually drive growth (not just which ones get the last click).
Own attribution modeling – Build and maintain multi-touch attribution that reflects the real customer journey. You'll challenge platform-reported numbers and reconcile discrepancies until we have a model we can trust.
Keep our data clean – Be the person who makes sure our marketing spend data is accurate. When someone asks "is this CAC number right?" you'll know the answer and how to fix it if it's not.
Analyze creative performance fast – Our creative team iterates quickly. You'll help them understand what's resonating (and what's not) so they can double down on what works.
Analyze subscriber economics – Monitor LTV, retention, and payback periods by cohort, channel, and country. Help us understand the unit economics that drive our business.
Grow with the role – As you get deeper into the business, you'll take on bigger problems: running mixed media models, forecasting performance, identifying international expansion opportunities, and partnering with lifecycle teams on retention strategies.

Required skills

2-4 years doing marketing or growth analytics – You've worked with acquisition data before and know your way around CAC, LTV, payback periods, and ROAS.
Strong SQL skills – You're comfortable querying large datasets in Snowflake (or similar) without needing hand-holding.
Experiment design experience – You know how to set up A/B tests, calculate statistical significance, and explain why incrementality testing matters.
Clear communication – You can translate complex analyses into insights that non-technical teams can act on. Bonus points if you can do this without making people's eyes glaze over.
Ownership mentality – You take pride in data quality and don't pass the buck when numbers don't add up.

Preferred skills

Experience building custom attribution models or working with attribution tools
Background in consumer subscription businesses (bonus if you've seen a team scale from startup to growth stage)
Familiarity with mixed media modeling (MMM)
Python or R skills for statistical analysis
Knowledge of paid social and paid search platform APIs
Genuine interest in what makes creative content perform
WHAT WE VALUE
Curiosity – you try different angles and attribution methods to uncover the real story
Healthy skepticism – you question platform-reported numbers and dig deeper to find ground truth
Speed – you can quickly turn around analyses when the creative team needs feedback
Partnership – you work well with marketers, creatives, and product teams who may not be as data-fluent
Additional Notes: Applicants must be eligible to work in the US.