Research Scientist Computational Economics

Key Skills

Econometrics, Machine learning techniques, Recommendation Systems

Job Description

We are looking for a Research Scientist with an economics background and past experience in machine learning. Past experience on recommender systems is a plus, but not a necessity. You will join a team of machine learning researchers whose focus is on innovating the Spotify experience through researching and developing ML technologies that power intelligent user experiences for long-term satisfaction. You will help us improve personalization experiences by striking a balance between users and creators through a combination of economic and ML skills, with the goal of creating a mutually beneficial experience for both.

You will be part of an interdisciplinary team focusing on ensuring that the foundations of Spotify technologies are at or above the state of the art and, in the process, redefine the state of the art for the field and contributing to the wider research community by publishing papers. Our team has strong ties internally to product groups as well as externally to the research community.

What You'll Do

• You will participate in groundbreaking research in the intersection between machine learning and economics
• You will apply your scientific knowledge to analyze and collect data, perform analyses, identify problems, devise solutions and construct methodologies, including metrics and best practices, and conduct experiments to validate these
• You work on practical applications such as recommendation, search, voice and language understanding, and areas related to music and talk audio
• You will work in collaboration with other scientists, engineers, product managers, designers, user researchers, and analysts across Spotify to design creative solutions to challenging problems
• You will have product impact, while working on and further developing a long-term research roadmap
• You will maintain a research profile through external engagement such as publishing, giving talks, and being an active community member at top conferences

Who You Are

• You have a PhD in one of computer science, machine learning, economics or related areas
• You have a strong knowledge of economics and machine learning. Past experience on recommender systems is a plus, but not a necessity
• You have publications in the Conference on Economics and Computation (EC), the economics tracks of IJCAI/AAAI, and the economics track of WWW, Econometrica, Management Science, Operations Research or related
• You possess proven hands-on skills in sourcing, cleaning, manipulating, analyzing, visualizing and modeling of real data
• You have a passion for making sense of user behavior, especially podcast and music content, using best available methods
• You are a creative problem-solver who is passionate about digging into complex problems and devising new approaches to reach results

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. This role will be based out of our London office, or remotely within the UK.
• 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 (https://spotifyjobs.com/work-from-anywhere)

Our global benefits

• Extensive learning opportunities, through our dedicated team, GreenHouse.
• Flexible share incentives letting you choose how you share in our success.
• Global parental leave, six months off - fully paid - for all new parents.
• All The Feels, our employee assistance program and self-care hub.
• Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify

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.