Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join an interdisciplinary team to conduct research in causal inference and machine learning.
- Company: Spotify aims to unlock human creativity through innovative technology and collaboration.
- Benefits: Enjoy flexible work options, including remote work and opportunities for professional growth.
- Why this job: Make a real impact on decision-making while contributing to cutting-edge research and innovation.
- Qualifications: Ph.D. in relevant fields with experience in causal inference and programming languages like Python or R.
- Other info: Engage with the research community through publishing and attending top conferences.
The predicted salary is between 36000 - 60000 £ per year.
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. 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 #J-18808-Ljbffr
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist - Advanced Causal Inference
✨Tip Number 1
Network with professionals in the causal inference and machine learning fields. Attend relevant conferences or webinars where you can meet people from Spotify or similar companies. Engaging with the community can lead to valuable connections and insights about the role.
✨Tip Number 2
Familiarise yourself with Spotify's current products and how they utilise causal inference. Understanding their existing tools and methodologies will help you demonstrate your knowledge during interviews and show how you can contribute to their mission.
✨Tip Number 3
Prepare to discuss your previous research and publications in detail. Be ready to explain your methodologies, findings, and how they relate to the work Spotify is doing. This will showcase your expertise and passion for the field.
✨Tip Number 4
Stay updated on the latest trends and advancements in causal inference and machine learning. Being knowledgeable about recent developments will not only enhance your discussions but also demonstrate your commitment to continuous learning in this rapidly evolving field.
We think you need these skills to ace Research Scientist - Advanced Causal Inference
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in causal inference and machine learning. Include specific projects or research that demonstrate your expertise and any publications in recognised communities.
Craft a Compelling Cover Letter: In your cover letter, express your passion for Spotify's mission and how your skills align with the role. Mention specific tools and methodologies you have used in past projects that relate to the job description.
Showcase Your Research Experience: Detail your research experience, especially any work related to causal inference. Highlight any collaborative projects and your contributions to interdisciplinary teams, as this is a key aspect of the role.
Prepare for Technical Questions: Be ready to discuss your technical skills in Python, R, and any relevant tools like TensorFlow or PyTorch. Prepare examples of how you've applied these skills to solve complex problems in your previous work.
How to prepare for a job interview at Spotify
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to causal inference and machine learning. Highlight any publications you've contributed to, as this demonstrates your active engagement with the research community.
✨Demonstrate Problem-Solving Skills
Expect to face complex problems during the interview. Prepare examples of how you've approached difficult challenges in your past work, particularly those involving data analysis and methodology development. This will showcase your critical thinking and creativity.
✨Familiarise Yourself with Relevant Tools
Make sure you are well-versed in tools like CausalML, EconML, TensorFlow, and others mentioned in the job description. Be ready to discuss how you've used these tools in your previous roles or projects, as practical experience is highly valued.
✨Engage with the Team's Mission
Understand Spotify's mission to unlock human creativity and think about how your skills can contribute to this goal. During the interview, express your enthusiasm for collaborating with interdisciplinary teams and how you envision your role in enhancing user and creator interactions.
