Data Scientist Fraud Payments

Key Skills

Java Programming, Python Programming, SQL, Apache Hadoop, Tableau, SPARK Programming, Large scale deployment

Job Description

As the world’s largest audio streaming subscription service, Spotify Premium enables millions of creators to make a living from their art by connecting them with the people who love it. It’s here that you’ll help grow our subscribers by growing the Premium experience, transforming user insights into meaningful innovations and ensuring our platform is available whenever and wherever our users want to listen.

Location: London or Remote EMEA

Job type: Permanent

We are looking for a Data Scientist to join our growing fraud prevention team, focused on 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 craft 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 necessary 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.

Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark.

Experience with a dashboard visualisation tool such as Looker, Google DataStudio, Tableau or similar.

Knowledge of Google BigQuery is a plus.

You are an entrepreneurial problem solver, able to work autonomously, capable of tackling loosely defined problems and translating them into practical application for diverse audiences

A communicative person who values building positive relationships with colleagues and enjoys collaboration.

Our global benefits

• Extensive learning opportunities, through our dedicated team, GreenHouse.
• Flexible share incentives letting you choose how you share in our success.
• Global parental leave, six months off - fully paid - for all new parents.
• All The Feels, our employee assistance program and self-care hub.
• Flexible public holidays, swap days off according to your values and beliefs.
• Spotify On Tour, join your colleagues on trips to industry festivals and events.