Senior Data Scientist - for the Soundtrap hub


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Posted 3 months ago

We are looking for a Senior Data Scientist to join the Soundtrap Product insights & data team! The team is a central team of data scientists, data engineers, and user researchers supporting the Soundtrap product organization with insights & data products. The team’s mission is to democratise and enable decisions backed by insights in all steps of the product development lifecycle.
You will analyze how users are engaging with Soundtrap, define success measures, monitor performance, and make data-driven recommendations that enable the Soundtrap organization to deliver a product that delights our users. You will use sophisticated data science techniques to build meaningful insights to support the business. In this role you will also get the opportunity to build central frameworks and Way of working to further improve the data driven culture at Soundtrap!

What you’ll do

  • Perform analyses on large sets of data to extract impactful insights that will help drive Soundtrap´s strategy across creator-facing products.
  • Establish learning agendas, measurement plans and success metrics in close coordination with product teams
  • Drive product strategy by leading foundational research & experimentation initiatives to develop a deeper understanding of our users
  • Work closely with cross-functional teams of data scientists, engineers, and others across the company
  • Communicate insights and recommendations through clear visualizations and presentations.
  • Contribute to the wider insights community at Spotify & Soundtrap by setting high-quality standards.
  • Help build central frameworks and processes contributing to the success of the Product insights practice throughout the company!

Who you are

  • You have at least 4+ years of experience in a similar data scientist role and a degree in science, computer science, statistics, economics or mathematics.
  • You’re a compelling storyteller who can communicate in succinct and inspiring ways to a variety of audience types to influence real world product or feature decisions.
  • You are a communicative person that values building strong relationships with colleagues and have the ability to explain complex topics in simple terms.
  • You enjoy mentoring and guiding others and have actively contributed to building Data science related frameworks optimally across an organization.
  • You thrive in a dynamic environment and are able to execute with autonomy.
  • You have proven experience working with SaaS products and product teams
  • You have deep understanding of a breadth of modeling techniques (e.g. regression models, causal inference in marketing and product launches, Bayesian techniques)
  • You have strong SQL skills and programmatic expertise, like R or Python
  • Experience with Docker, AWS/Google Cloud Platform infrastructure, Apache Spark/Beam
  • Expertise in machine learning and data engineering concepts in production and at scale.
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 320 million users.
Job tags: AWS Economics Engineering Machine Learning Marketing Python R Research Spark SQL
Job region(s): Europe
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