Spotify - Data Scientist II
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Requirements
• 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.
Responsibilities
• 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.
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