The Music Mission team is responsible for shaping how music is created, managed, and experienced on Spotify. Within this, the Rights Management team builds products that help rights holders seamlessly interact with Spotify's platform. You'll join a cross-functional group spanning R&D, Partnerships, Legal, and Operations, working together to make rights management more scalable, transparent, and effective for creators and their teams.

You will work closely with engineering, design, and insights teams to build and improve catalog and rights management tools used by rights holders and creators. You will define product strategy and roadmap, balancing user needs, business priorities, and technical scalability. You will lead the end-to-end product lifecycle, from discovery and prototyping through launch and iteration. You will set clear success metrics and use data to guide product decisions and measure impact.

You will partner with cross-functional stakeholders to align on priorities and deliver complex, long-term initiatives. You will share expertise on music rights and industry standards to inform product direction and feasibility. You will engage with external partners and the broader music industry to support adoption and gather feedback.

You are experienced in product management and care deeply about building thoughtful, user-centered products. You have worked on platform or music-related products and understand complex ecosystems. You are comfortable communicating across different audiences, from executives to engineers. You collaborate effectively across teams and build strong working relationships.

You can navigate ambiguity, make informed trade-offs, and bring clarity to complex problems. You are organized and able to manage multiple priorities in a fast-moving environment. You care about improving experiences for artists, songwriters, and their teams. You are comfortable working with distributed teams across time zones. You have experience with rights management systems, digital media platforms, or B2B products. You are familiar with industry tools such as Content ID, Rights Manager, or similar systems.

This role is based in New York. We offer you the flexibility to work where you work best! There will be some in-person meetings, but still allows for flexibility to work from home.

The United States base range for this position is $119,424–$170,606 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.

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We're interested in connecting with experienced Product Managers who are passionate about building intuitive, impactful products that serve public sector partners and the communities they support.

This posting is intended to build relationships with candidates for potential future openings and does not represent an active role at this time.

Responsibilities

• Defining and executing product strategy for tools used by government partners
• Collaborating cross-functionally with Engineering, Design, Sales, and Account Management teams
• Gathering and synthesizing customer insights to shape roadmap priorities
• Translating user needs into detailed requirements, use cases, and product flows
• Launching new (0→1) products and iterating based on user feedback
• Establishing and tracking key success metrics to measure product impact
• Ensuring consistency and quality across a broader suite of integrated products
• Acting as the internal advocate for government users and their operational needs

What We’re Generally Looking For

• 5–7+ years of experience in Product Management, particularly in enterprise or B2B products
• Experience launching new products (0→1) and scaling them successfully
• Strong analytical mindset and ability to use data to inform decisions
• Ability to define clear strategy, priorities, and goals and drive execution across teams
• Excellent communication skills across technical and non-technical stakeholders
• Experience working in Agile development environments
• Comfort operating independently in fast-paced, evolving environments

Compensation (Future Opportunities – California)

For future Senior Product Manager roles based in California, the expected base salary range is approximately $160,000 – $185,000 annually.

Benefits

Wonderschool offers a competitive benefits package, which may include:

• Health benefits with up to 100% coverage for employee premiums and up to 80% for dependents
• Wifi, employee wellness, and co-working reimbursements
• Flexible PTO, paid holidays, and mental wellness days
• Competitive parental leave (eligible after 6 months of employment)
• A fully remote, highly collaborative work environment
• A mission-driven culture focused on ownership, impact, and growth

Additional Notes

This is not an active job opening and does not guarantee an interview or offer.

Role scope, level, and compensation may vary based on business needs.

Candidates may be contacted if and when a relevant opening becomes available.

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Location

San Francisco

Employment Type

Full time

Department

Data Science

Compensation

• $293K – $515K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

OpenAI’s mission is to ensure AI benefits all of humanity. ChatGPT for Work supports that mission by helping more people access real leverage from AI in their day-to-day jobs—so they can spend less time on busywork and coordination, and more time on the work that’s meaningful and additive. We’re building an AI-native workspace where AI acts as a superassistant for everyday tasks and a coworker you can hand work off to—then review, edit, and approve with confidence.

About the Role

As the Data Scientist for ChatGPT for Work, you’ll shape product strategy through data: uncover the user problems most worth solving, form sharp hypotheses about what will move team and business outcomes, and influence what we build next by presenting compelling recommendations grounded in rigorous evidence. You’ll be the DRI for the Work insight → strategy → experiment → decision loop—defining what “success” means for teams, pinpointing the highest-leverage adoption and retention bottlenecks, and turning signals into clear product direction.

You’ll partner closely with Product, Engineering, Research, and Finance to ensure our metrics are trusted, our experimentation is rigorous, and our insights turn into shipped improvements.

Responsibilities

• Own the core KPI framework for ChatGPT for Work, spanning onboarding, activation, engagement, retention, and expansion, as well as quality/trust guardrails.

• Build end-to-end funnels that identify where individuals and teams succeed or get stuck, from first workspace setup through repeat usage and long-term team adoption and value creation.

• Define and operationalize “time-to-value” and collaboration loop metrics, and connect them to business outcomes.

• Design and evaluate experiments and rollouts to quantify the impact of product changes across key Work surfaces and flows.

• Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct.

• Translate complex analysis into clear, compelling insights that shape product strategy and roadmap decisions.

• Help establish data science standards and best practices for measuring human–AI collaboration and AI-native work outcomes.

• Partner with other data scientists across the company to share learnings and raise the bar on measurement, experimentation, and decision-making.

Requirements

• 10+ years in data science / analytics in in high-velocity product environments

• Direct experience working on B2B products (SaaS, collaboration/workspace, developer tools, or enterprise)

• Expert SQL + strong Python

• Strong experimentation + causal inference judgment (incl. when clean A/B tests aren’t feasible)

• Strong product sense/taste: can turn messy signals into crisp hypotheses and roadmap direction

• Proven ability to inspire and influence PM/Eng/Design + leadership through data storytelling

• Autonomous operator who sets the insights/measurement agenda

• Excellent executive communication; thrives in ambiguous, fast-moving environments

• AI-native operator (non-negotiable): “super AI-pilled”—first to adopt new AI tools, uses them daily to increase throughput, and turns them into durable org workflows

Nice-to-haves

• Experience with agentic and/or AI-native B2B products (agents, copilots, workflow automation, AI collaboration)

• Experience measuring AI product quality, trust, and human-AI interaction signals

• Familiarity with enterprise admin/security constraints and how they shape adoption

• Experience with

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