Data Scientist II, Payments Fraud
London
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!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, redefining user insights into meaningful innovations and ensuring our platform is available whenever and wherever our users want to listen.
We are looking for a Data Scientist to join our fraud prevention team, passionate about using data science techniques to prevent fraud and help the business to grow, in a safe and scalable way. As part of the Commerce team, you will help craft and deliver our global fraud strategy.
You will work with a global team of world-class 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
- Apply your expertise in Machine Learning to develop, refine, and implement real time models that will improve our ability to predict and prevent fraud and abuse.
- Apply your expertise in the domains of payments and fraud to improve Spotify's strategies for fraud mitigation, and contribute towards aligning our fraud prevention practices with industry standards.
- Assess the potential opportunity and business impact of initiatives related to fraud and abuse. Your analysis will help guide strategic decisions and prioritise projects based on their potential return on investment and alignment with Spotify’s goals.
- Communicate and share insights with stakeholders across the business. Your ability to present sophisticated data in a clear and understandable manner will ensure that all parties are advised and able to make data-driven decisions.
- Collaborate closely with our Engineering and Product teams to bring about meaningful changes to our systems.
- Implement and enhance metrics to continuously supervise and assess the performance of our fraud prevention strategies.
- Continually seek ways to improve and innovate our setup. By researching new technologies and methods across fraud prevention, data science, and data visualisation, you will play a pivotal role in growing the technical capabilities of our team and enhancing our fraud prevention efforts.
Who You Are
- 3+ years experience in a data science role, with at least 1 of those years of experience in a fraud role.
- A Degree in Computer Science, Engineering, Mathematics, Statistics, Economics or another quantitative field.
- Experience working with machine learning in the fraud prevention or security domain.
- Proficiency with Python for data science and SQL.
- Experience with a dashboard visualisation tool such as Looker, Tableau or similar.
- Knowledge of Google BigQuery is a plus.
- Someone who loves solving business problems as much as a data problems
- 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
- You'll be based in Stockholm, Sweden or London, UK.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: BigQuery Computer Science Economics Engineering Looker Machine Learning Mathematics Python R R&D Research Security SQL Statistics Streaming Tableau
Perks/benefits: Career development
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