Spotify is seeking a Data Scientist II to join Product Trust Insights (PTI) within Trust & Safety. PTI accelerates Spotify innovation by providing safety research, risk measurement, and evidence-based recommendations that enable R&D teams to confidently expand into new products, markets, and technologies.
PTI's research informs how Spotify designs, launches, and improves features across the platform, with a particular focus on AI-powered experiences, recommendations, social and messaging surfaces, and the safety needs of younger users. Our work helps product teams understand where risks concentrate, which user segments are most affected, and which interventions improve outcomes.
This role will partner with other Trust & Safety teams to ensure that product and policy decisions are grounded in rigorous evidence. The work spans pre-launch risk assessment, evaluation of AI features and agentic systems, longitudinal safety measurement, and research into how high-risk user populations experience the platform. Trust & Safety's mission is to keep Spotify safe for creators, advertisers, and listeners, and PTI's contribution is the evidence base that makes safer product decisions possible.
What You'll Do- Lead end-to-end research and measurement projects that evaluate the safety of new and existing features, from scoping through delivery of actionable recommendations
- Design and generate data for product risk assessments, stress tests, and evaluation of AI-powered features, including generative and agentic experiences
- Develop longitudinal trust and safety metrics and use them to evaluate the effectiveness of product interventions over time
- Translate complex research findings into clear narratives, tools, and recommendations for product, policy, and leadership audiences
- Partner with product safety specialists, policy advisors, product leads, and engineering counterparts to ensure product launches reflect user safety needs and support thoughtful, "no regrets" design
- Build and improve evaluation methods, including LLM-based evaluation approaches, behavioral instrumentation, and measurement frameworks in collaboration with data scientists and engineers
- You will work closely with product managers, designers, engineers, policy specialists, researchers, and other data scientists. Your work will help inform decisions that often involve senior leadership.
Who You Are- You have 3+ years of experience leading data science or research projects with a focus on safety, integrity, responsible AI, fairness, or a related domain
- You are experienced with SQL and Python and are comfortable working across quantitative and qualitative evidence
- You have hands-on familiarity with modern AI and machine learning systems, including recommendation systems and large language models, and understand how risks emerge from system design
- You are comfortable scoping ambiguous problems, including early-stage or zero-to-one research areas, and prioritizing them in a fast-moving environment
- You communicate clearly with both technical and non-technical audiences, including explaining methodological choices to policy partners and leadership
- You care about turning research into practice and are comfortable making concrete, evidence-based recommendations
- You bring a thoughtful perspective on responsible product innovation and how to measure and improve platform safety
Where You'll Be- This role is based in New York or Boston
- 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
- This team operates within the Eastern Standard time zone for collaboration
The United States base range for this position is $117,000 - $167,000 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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here:
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