2024 Summer Internship, Causal Inference Research Scientist (London)

London

Applications have closed

Spotify

We grow and develop and make wonderful things happen together every day. It doesn't matter who you are, where you come from, what you look like, or what music you love. Join the band!

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Spotify is looking for enthusiastic students with a passion for music and an ambition to go far. This isn't just any internship! Our paid internship program will give you the chance to gain in-depth knowledge of what it's like to be a Spotify employee as well as get the opportunity to see the technology side of a fast growing company! Our summer internships will last for approximately 10 weeks this summer and start in the beginning of June.
Spotify’s 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 opportunity to enjoy and be inspired by it. We are looking for a Research Scientist intern 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 to 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 are pursuing 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, etc., is a strong plus
  • You have experience with hands-on skills in sourcing, cleaning, manipulating, analysing, visualising and modelling of real data
  • You currently have valid work authorization to work in the country in which this role is based that will extend from June to August 2024
  • 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 will require you to work out of our London Office 
  • Working hours? We operate within GMT for collaboration 
Our paid summer internships last for approximately 10 weeks and start at the beginning of June. The last day to apply is March 15th 2024 at 9 AM ET.  
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.

Tags: Causal inference Computer Science Engineering ICLR ICML Machine Learning Mathematics NeurIPS Physics Python PyTorch R Research Scikit-learn Streaming TensorFlow

Perks/benefits: Conferences

Region: Europe
Country: United Kingdom
Job stats:  73  7  0

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