Lead Data Scientist - Payment Analytics
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!We are looking for a payments analytics expert to lead and grow a distributed team of Data Scientists within the Payments team. You and the team will use sophisticated techniques on large sets of data to create practical business insights and recommendations that inform our payments optimisation strategy.
You will work with a distributed team of world-class analysts, data scientists, business managers, product managers and engineers. We are all passionate about what we do and move forward with high impact projects at a high pace. Learning and improving is part of our daily routine, and you will be free to develop your skills and ways of working.
What you'll do
- Lead, manage and grow a distributed team of Data Scientists within the Payments Team.
- Develop in depth knowledge of Spotify’s data sources and payment systems to gain insights into payments performance and identify optimisation opportunities.
- Closely collaborate and partner with senior leaders across multiple teams to understand and drive critical initiatives.
- Work closely with our Engineering, Product and Analytics teams to craft data structures and pipelines, which will empower research and analysis.
- Engineer novel datasets and features, and improve existing ones, with a focus on enabling the flexible analysis of payments performance on our platform.
- Work with the engineering team to implement new ETL pipelines, and data infrastructure improvements, as needed
- Define metrics and KPIs to track payments performance, keeping the Payments team informed with data-driven research on optimisation initiatives and challenges.
- Work from anywhere in EMEA, with occasional travel to our offices in London, Stockholm and New York.
Who you are
- 5+ years experience in a data science role, preferably in at least one e-commerce or payments organisation.
- A background in Computer Science, Analytics Engineering, Mathematics, Statistics, Economics or another quantitative field.
- Leadership and management experience, as well as strong project management skills.
- Experience collaborating with partners to measure the impact of payments optimisation initiatives and presenting those findings in coherent recommendations.
- Proficiency with Python or similar programming languages and associated data science packages.
- Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark.
- Experience with dashboard visualisation tools such as Tableau, Looker, Google Data Studio or similar.
- Intellectually curious, creative and diligent - you enjoy thinking about the business as much as the data!
Where you'll be
- We are a distributed workforce enabling our band members to find a work mode that is best for them!
- Where in the world? For this role, it can be within the EMEA region in which we have a work location and is within working hours.
- Working hours? We operate within the Central European and GMT time zones for collaboration and ask that all be located that time zone.
- Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
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 381 million users.
Tags: Computer Science Data Studio Distributed Systems E-commerce Economics Engineering ETL Hadoop KPIs Looker Mathematics Pipelines Python RDBMS Research Spark SQL Statistics Streaming Tableau
Perks/benefits: Career development Flex hours Flex vacation
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