Job Description

Tech Research
Spotify's mission is to unlock the potential of human creativity. We are looking for a Research Scientist specialising in causal inference and machine learning to help us with this mission. Successful applicants are encouraged to conduct research in causal inference and apply causal inference techniques to craft and build tools to help creators and Spotify teams make better decisions. This is an opportunity to improve decision making with causal inference by collaborating with multiple teams to reshape Spotify's existing products and develop new ones.
Locations


London
Stockholm
Job type


Permanent


Our team is interdisciplinary, focusing on ensuring that the foundations of Spotify technologies are at or above the groundbreaking. In the process we aim to redefine and improve the state-of-the-art for the field and contribute to the wider research community by publishing papers.
What You'll Do

Join an interdisciplinary team passionate about making every user and creator interaction with Spotify outstanding and in the process pushing innovation and contributing to the wider research community by publishing papers You will participate in innovative fundamental and applied research in causal inference, machine learning, and related fields You will apply your scientific knowledge to analyze and collect data, perform analyses, identify problems, devise solutions and construct methodologies, including metrics and best processes, and conduct experiments to validate these You will be a valued member of an autonomous, cross-functional team working in collaboration with other scientists, engineers, product managers, designers, user researchers, and analysts across Spotify to craft creative solutions to challenging problems External engagement such as publishing, giving talks, and being an active community member at top conferences is actively encouraged
Who You Are

You have a Ph.D. degree in Computer Science, Physics, Mathematics, Engineering, with a focus on fundamental or applied causal inference, or equivalent experience. Previous proven industry experience is a plus You have publications in relevant communities such as UAI, CLeaR, ICML, ICLR, NeurIPS, AAAI, WWW, KDD, or related A problem-solver with experience with Python, R, or similar languages. Experience with tools like CausalML, EconML, TensorFlow, PyTorch, Scikit-learn, Ray, etc., is a strong plus You have experience with hands-on skills in sourcing, cleaning, manipulating, analysing, visualising and modelling of real data. Experience with SQL is a plus You are a creative problem-solver who is passionate about digging into complex problems and devising innovative ways to reach results
Where You'll Be

This role is based in Stockholm (Sweden) or London (UK) 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
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


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 500 million users.


Learn more about our culture