Research Scientist, Algorithmic Responsibility

San Francisco, CA /
Data and Analytics – Trust & Safety /
Permanent
Spotify is seeking a Machine Learning Research Scientist to join our Algorithmic Impact & Responsibility effort. This effort is focused on empowering Spotify teams to assess the algorithmic impact of their products on audio culture, avoid algorithmic harms and unintended data or machine learning side-effects, and better serve worldwide audiences and creators. 

Your role will be to further shape algorithmic responsibility at Spotify through research and development of methods to ensure equitable algorithmic outcomes, and collaborate with product teams to put this into practice. You will ensure a better understanding of Spotify’s impact, as well as product-specific auditing or intervention methods focused on equity in music and podcasts. You will increase our abilities to understand the effects of data, machine learning and recommendation choices on listener and creator communities.

Significant cross-functional collaboration is expected, and you’ll deeply influence the way that algorithmic responsibility is operationalized at Spotify. You will work with a variety of teams, including other researchers, data scientists, Machine Learning engineers, product teams as well as policy and legal constituents. You will be communicating with internal and external stakeholders with differing perspectives and needs, and will translate complex open questions into concrete methods, analysis and action.

What you'll do

    • Develop research and auditing methods related to tech responsibility, algorithmic fairness and Machine Learning impact on the music and podcast industry. 
    • Ensure the team’s state of the art understanding of Machine Learning fairness auditing, including privacy-centric methods, and ensure our participation in relevant research communities.
    • Develop methods to assess and address potential data and model inequities, together with policy, product and research teams.
    • Contribute to the algorithmic fairness and responsibility research community through publishing.
    • Develop methods and build tools for strategic projects focused on algorithmic and content programming responsibility.
    • Train models and evaluate their effectiveness against metrics that encapsulate real and immediate objectives.
    • Apply techniques and methods from literature that require auditing, anomaly detection, classification, ranking, and A/B/N testing.
    • Communicate results and recommendations to both specialized and technical internal and external audiences, but also non-technical audiences, through clear deliverables and presentations. 
    • You must be comfortable reviewing or being exposed to sensitive content, and having related conversations with teams.

Who you are

    • You have a PhD in a field related to Machine Learning, algorithmic responsibility, computational social science, data science, or equivalent experience. 
    • You are up to date on the state of the art in fairness auditing and Machine Learning methods. You actively participate and publish in related communities.
    • You have demonstrated expertise within tech responsibility, and how Machine Learning can impact society. 
    • You deeply care about the translation of abstract research, or high-level calls to action into concrete methods, and practice. You are comfortable making concrete recommendations to product teams, on the basis of solid research. 
    • You have experience communicating complex topics to audiences with different backgrounds. You can educate and communicate convincingly, both to less experienced audiences as well as very experienced decision makers.  
    • You are passionate about music and popular culture, cultural equity and impact. Previous experience in either representation in music, media, entertainment, cultural heritage, or projects related to misinformation, communities or radicalization are a plus.
    • You are capable of tackling very loosely defined problems, and are comfortable owning an ambitious long-term research agenda, while ensuring delivery of concrete short-term milestones and impact in collaboration with researchers with different specialities.
You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service with a community of more than 345 million users.