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- Tasks: Join a team to conduct research in causal inference and machine learning.
- Company: Spotify aims to unlock human creativity through innovative technology.
- Benefits: Enjoy flexible work options and the chance to collaborate with diverse teams.
- Why this job: Make a real impact on decision-making while contributing to groundbreaking research.
- Qualifications: Ph.D. in relevant fields; experience with Python, R, and data analysis is preferred.
- Other info: Opportunities for publishing and engaging with the research community.
The predicted salary is between 43200 - 72000 £ 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.
Research Scientist - Advanced Causal Inference employer: Spotify
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist - Advanced Causal Inference
✨Tip Number 1
Familiarise yourself with the latest research in causal inference and machine learning. Being well-versed in recent publications and methodologies will not only enhance your understanding but also demonstrate your commitment to the field during discussions.
✨Tip Number 2
Engage with the community by attending relevant conferences or webinars. Networking with professionals in the field can provide valuable insights and connections that may help you stand out as a candidate.
✨Tip Number 3
Showcase your hands-on experience with data analysis tools and programming languages like Python or R. Be prepared to discuss specific projects where you've applied these skills, as practical experience is highly valued.
✨Tip Number 4
Prepare to discuss how you would approach real-world problems using causal inference techniques. Think of examples where you could apply your knowledge to improve decision-making processes at Spotify, as this will highlight your problem-solving abilities.
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 in causal inference and related fields. Highlight any innovative solutions you've developed and how they contributed to previous teams or projects.
Prepare for Technical Questions: Anticipate technical questions related to causal inference and machine learning during the interview process. Be ready to discuss your problem-solving approach and provide examples of how you've tackled complex data challenges.
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 problem scenarios during the interview. Practice articulating your thought process when tackling these problems, showcasing your analytical skills and creativity in finding solutions.
✨Familiarise Yourself with Relevant Tools
Make sure you are well-versed in tools like Python, R, CausalML, and TensorFlow. Be ready to discuss how you've used these tools in past projects, as practical experience is highly valued.
✨Engage with the Team's Mission
Understand Spotify's mission and how your role as a Research Scientist fits into it. Be prepared to discuss how your work can contribute to improving decision-making for creators and users alike, aligning your goals with the company's vision.
