Payments Fraud Data Scientist (Remote Eligible - EMEA)
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 Data Scientist to join our growing fraud prevention team, passionate about using data insights to prevent fraud and help the business to grow, in a safe and scalable way. As part of the Payments team, you will help shape and deliver our global fraud strategy.
You will work with a global 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:
- Develop in depth knowledge of Spotify’s data sources and payment systems to gain insights into user behaviour and contribute to the fraud strategy.
- Discover signals, test new ideas and implement new features in our realtime machine learning model.
- Build relationships and work closely with Spotify’s Engineering, Product and Analytics teams, inspiring changes to data sources and systems that are vital to deliver on the fraud strategy.
- Research new technologies and methods across fraud prevention, data science and data visualisation to continuously grow the technical capabilities of the team
- Keep the Payments team informed with data-driven research on key fraud prevention initiatives and challenges.
- Work from anywhere in EMEA, with occasional travel to our offices in London, Stockholm and New York.
Who You Are:
- 2+ years experience in a data science role, preferably in at least one e-commerce or payments organisation.
- A Degree in Computer Science, Engineering, Mathematics, Statistics, Economics or another quantitative field.
- Experience working with algorithms for classification, regression, clustering and anomaly detection, preferably in the fraud prevention or security domain.
- Proficiency with Python or similar programming languages and associated data science packages.
- Solid understanding of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark.
- Experience with a dashboard visualisation tool such as Tableau, Qlik Sense or similar.
- Knowledge of Google BigQuery is a plus.
- An ambitious thinker, able to work autonomously, capable of tackling loosely defined problems and translating sophisticated thinking into practical application for diverse audiences.
- A communicative person who values building strong relationships with colleagues and enjoys collaborating with others.
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
- Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about about our Work From Anywhere options here.
- Working hours? We operate within the Central European time zone for collaboration
- We ask that our team members be located within Greenwich Mean time zone, Central European time zone, or Eastern European standard time zone for the purposes of our collaboration hours
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 345 million users.
Tags: BigQuery Classification Computer Science Distributed Systems E-commerce Economics Engineering Hadoop Machine Learning Mathematics Python Qlik RDBMS Research Security Spark SQL Statistics Streaming Tableau
Perks/benefits: Career development
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