Machine Learning Research Scientist - Algorithmic Impact & Responsibility
New York, NY /
Data and Analytics – Trust & Safety /
Spotify is seeking an experienced Researcher to join our Algorithmic Impact & Responsibility effort. This effort focuses 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, set policy and processes, while developing practical methods to ensure equitable outcomes with product teams in practice. You will ensure a better understanding of Spotify’s impact, as well as product-specific auditing methods that encourage 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, including topics such as information access and community growth.
Significant cross-functional collaboration is encouraged, 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, product teams as well as policy and legal constituents. You will be communicating with internal and external partners with differing perspectives and needs, and will translate sophisticated open questions into concrete analysis and action.
What you'll do
- You will develop and iterate policy and auditing processes related to tech responsibility, algorithmic fairness and representation in the music and podcast industry.
- Develop strategy around cultural equity in audio and Machine Learning projects.
- Together with policy, product and research teams, growing and evolving methods to assess and address potential data, model and metric inequities.
- Define success measures and build tools that predict and supervise performance of strategic projects passionate about algorithmic and content programming responsibility.
- Communicate insights and recommendations to both highlight technical specialized internal and external audiences, but also non-technical audiences, through clear visualizations and presentations.
- Contribute to the algorithmic fairness and responsibility research community through publishing.
- You must be comfortable reviewing or be exposed to sensitive content, and having related conversations with teams.
Who you are
- You have validated expertise within tech responsibility and the intersection of algorithmic bias, gender, and racial equity. You actively participate in related communities.
- You have extensive leadership experience.
- 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 teams, on the basis of solid research. 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 in general. You ideally have previous experience in either representation in music, media, entertainment, cultural heritage, or projects related to misinformation spread, communities or radicalization.
- You have extensive experience communicating sophisticated topics to internal and external audiences with different backgrounds.
- You are capable of tackling very loosely defined problems, and are comfortable leading and owning a results-oriented long-term research agenda, while ensuring delivery of concrete short-term breakthroughs and impact.
- You have a PhD in a field related to (tech) law or policy, communication, information science, media studies, algorithmic responsibility, computational social science, HCI and/or Machine Learning, or equivalent experience.
- You have experience leading high-profile projects that aim to solve analytical problems using data from different sources, and mixed methods.
Where you'll be
- We are a distributed workforce enabling our band members to find a work mode that is best for them!
- Where in the world? For this role, it can be within the Americas region in which we have a work location
- Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
- Working hours? We operate within the Eastern Standard time zone for collaboration
Spotify is an equal opportunity employer. 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.