Senior UX Researcher, Mixed Methods (Quant-Leaning)

Suno•New York, NY

8d•$176,000 - $220,000•Onsite

About The Position

Suno is seeking a Senior Mixed Methods UX Researcher in New York to focus on understanding user behavior related to monetization and subscription retention. This role is quant-leaning and requires expertise in survey science and measurement techniques such as conjoint analysis, MaxDiff, price sensitivity testing, and longitudinal tracking. The researcher will also conduct qualitative studies when necessary and will partner closely with Product Managers and leads focused on growth, monetization, and subscription revenue. The position is designed for someone with deep methodological knowledge to provide measurement insights that inform pricing, packaging, and conversion decisions. The researcher will be responsible for deciding the appropriate methodology for research questions and communicating limitations to stakeholders. Key responsibilities include owning survey methodology as a craft, designing and executing advanced quantitative studies, making pricing and packaging decisions defensible through rigorous measurement, building and evolving longitudinal measurement systems, explaining conversion, retention, and churn by combining attitudinal and behavioral data, owning the measurement layer of segmentation, leading qualitative work when depth is required, advising on method selection across the organization, and communicating findings into clear, actionable narratives with recommendations.

Requirements

5+ years conducting quantitative research in a product environment, with real qualitative range alongside it
Degree in Statistics, Behavioral Science, Psychology, Sociology, HCI, Economics, or a related quantitative field
Genuine depth in the end-to-end survey process: construct definition, instrument design, logic and branching, quotas, bias mitigation, weighting, and analysis
Hands-on experience with advanced survey methodologies, specifically choice-based conjoint, MaxDiff, TURF, price sensitivity methods, and monadic or sequential monadic testing. Not "familiar with," but studies you designed and defended
Experience building longitudinal measurement frameworks: trackers, benchmarks, perception scales, composite health metrics
Comfortable in SQL and in Python or R for analysis, and able to work directly against a warehouse rather than waiting on a pull
Fluent in the statistics that come up in practice: regression, ANOVA, hypothesis testing, and knowing when your sample can't carry the claim
Proficient in qualitative methods, and clear-eyed about when the right answer is twelve interviews rather than a survey
Strong product sense and an outcome-centric mindset. You bring structure to questions that arrive vague
Persuasive with senior stakeholders, including when the finding is not what they hoped for
Self-directed with a high tolerance for ambiguity and speed. We have a research team, but everyone here works with the autonomy of a solo researcher at a startup
Excited by consumer products, creativity, music, and AI
Must be authorized to work in the United States
Must be willing to work 5 days per week at our New York City office

Nice To Haves

Advanced degree with methodological training, combined with industry experience
Experience in subscription consumer businesses, especially on pricing, packaging, conversion, retention, or win-back
Experience with survey platforms and conjoint tooling (Conjointly, Sawtooth, Qualtrics, Sprig, or similar)
Experience with causal inference and experimentation, including covariate adjustment, and comfort reading an A/B readout critically
Experience standing up measurement infrastructure somewhere it didn't exist
Background in consumer audio, music, or social products
Experience researching AI and generative products, where user mental models are still forming
Bonus points if you've used Suno to make music

Responsibilities

Own survey methodology as a craft - Design and run advanced quantitative studies end to end: conjoint, MaxDiff and TURF, price sensitivity, monadic testing, segmentation, driver and key-driver analysis. Own sampling, quotas, logic, bias mitigation, weighting, and the analysis that follows.
Make pricing and packaging decisions defensible - Partner directly with the PMs and leads owning subscription revenue to turn packaging, tier, and pricing questions into studies that produce an answer they can act on, with honest confidence intervals attached.
Build and evolve our longitudinal measurement systems - Extend our always-on measurement program: satisfaction and sentiment trackers, product health composites, perception scales, and the reporting cadence that puts them in front of leadership every month. Make the trends trustworthy enough that people change plans because of them.
Explain conversion, retention, and churn - Combine attitudinal data with behavioral data in Snowflake to answer why people convert, why they cancel, and what would bring them back. Work with data science as a peer, not a requester.
Own the measurement layer of segmentation - Turn behavioral clusters into segments with attitudinal meaning: what each group is trying to do, what they value, and what they'll pay for. Keep those segments alive and validated rather than one-off.
Lead qualitative work when depth beats scale - Run interviews, diary studies, and concept work to define the right constructs before you measure them, and to explain the findings the numbers can't.
Advise on method selection across the org - Act as the internal consultant on when a question needs qual, quant, an experiment, or nothing at all. Push back on studies that won't change a decision.
Communicate so it lands - Turn multi-source data into a clear narrative with a recommendation. Dashboards and decks are the delivery mechanism, not the output.