Senior UX Researcher, Mixed Methods (Quant-Leaning)

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where there is real specific content. We need to parse the posting. First, there is an "About Suno" paragraph, but that is not a section heading we need; we only output sections as per rules. The "About The Role" is a heading we should use as

About the role

and then content. Then "What You'll Do" corresponds to Responsibilities. Then "Who You Are" corresponds to Qualifications/Requirements? Possibly "Who You Are" is qualifications. Then "What You'll Need" could be Requirements or Skills? Might be Requirements. Then "Additional Notes" includes work authorization, location, etc. Then "Perks & Benefits" is Benefits. Then "Compensation" is Pay. Schedule: maybe not present; they mention "You must be willing to work 5 days per week at our New York City office" which is schedule info (5 days per week). So we can include Schedule section with that. We must not repeat job title as heading. No Job ID. We must remove boilerplate: EEO etc. Remove "Suno is proud to be an Equal Opportunity Employer..." etc. Also remove "Additional Notes" maybe but we need to keep work auth and location? Those are minor metadata; we can fold into a short

maybe under Schedule or separate? The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So we can include a short

for work auth and location maybe under a generic paragraph before sections? But we need to output only HTML fragment; we can include a

at top for those minor metadata. But we must preserve ALL substantive information; not invent or summarize away detail. So we need to keep details about responsibilities, qualifications, etc. We need to use

• for any list of duties/requirements/benefits. So we need to convert bullet-like sentences into lists. Let's extract content. About The Role paragraph: "We have 100 million people who have made a song. We know far less than we should about which of them will pay us, what they'd pay for, and what makes someone decide that a subscription is worth keeping. We're looking for a Senior Mixed Methods UX Researcher in New York to own that problem. This role is quant-leaning by design. You'll be the methodological depth on our team for survey science and measurement: choice-based conjoint, MaxDiff, price sensitivity, monadic and sequential monadic concept testing, driver analysis, and the longitudinal trackers that tell us whether the user experience is actually getting better over time. You'll also run qualitative work when the question needs depth rather than scale, and you'll know the difference. Your closest partners will be the PMs and leads working on growth, monetization, and subscription revenue. These are people making pricing, packaging, and conversion decisions on a weekly cadence, and they need measurement that can keep up. This is a hire for depth we don't have, not for extra hands. You'll be the person who decides what a question can and cannot support, and who says so when a stakeholder wants a number the design can't give them." We'll put that as prose under

  About the role

  maybe as

  . What You'll Do (Responsibilities): List items: - 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. We'll make each bullet a

• . Who You Are (Qualifications): List: - 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 We'll make each bullet a
• . What You'll Need (Requirements/Skills): List: - 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 We could treat as Requirements or Skills. The instruction: Use headings for Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We have both Qualifications and Requirements; we can map "Who You Are" to Qualifications, "What You'll Need" to Requirements. Skills maybe not separate; we could omit Skills heading if no specific skills list beyond those. But we could put some under Skills if we want. However we should only include sections when there is real specific content. We have content for Qualifications and Requirements. We could also include Skills if we want to list technical skills like SQL, Python/R, survey platforms, etc. But those are already in Requirements. Might be redundant. Better to have Qualifications and Requirements sections. Benefits: "Perks & Benefits For Full-Time Employees" list: - 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) We'll make each bullet
• . Pay: "Compensation The annual salary range for this role is $176K – $220K (before equity)". We'll put as

  maybe. Schedule: "You must be willing to work 5 days per week at our New York City office". Also "You must be authorized to work in the United States". That's more about eligibility. We'll put schedule: 5 days per week in NYC office. We'll also maybe include work authorization as a short

  under Schedule or separate? The instruction says fold minor metadata into a short

  or drop it. So we can include a short

  for work authorization and location maybe under Schedule or as a separate

  before sections. But we need to preserve all substantive information; work authorization is substantive but minor. We'll include a

  after the headings maybe before sections: "

  Must be authorized to work in the United States and willing to work 5 days per week at our New York City office.

  " That covers both. Now we need to output only HTML fragment, no /, no markdown fences. Structure:

  About the role

  ...paragraph...

  Responsibilities

  • ...
  ...

  Qualifications

  • ...
  ...

  Requirements

  • ...
  ...

  Benefits

  • ...
  ...

  Pay

  The annual salary range for this role is $176K – $220K (before equity)

  Schedule

  Must be authorized to work in the United States and willing to work 5 days per week at our New York City office.

  We need to ensure we don't include empty sections. All have content. Check for any boilerplate we must remove: EEO etc removed. Also "Listen to the Suno version of this role! https://suno.com/s/xVPN3bUuZ4xbO8M9" is a link; we should keep? It's not boilerplate but maybe considered promotional; but it's substantive? It's a link to listen to role. Might be considered extra but not required to remove. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. That link is not those; we could keep it but it's not part of sections. Could be placed under About the role as a link? It appears after About Suno paragraph. Might be considered part of About Suno. We could include it as a

  with link. But we already have About the role section; we could add that link there. However the instruction says preserve ALL substantive information; do NOT invent or summarize away detail. So we should keep that link. Where to place? It appears after the About Suno paragraph and before About The Role. It's a link to listen to the role. Could be placed under About the role as a

  with the link. We'll include it. Also there is "About