Data Scientist II - User Fraud

Toronto
Data and Analytics – Platform /
Remote
We’re looking for a Data Scientist to join the band. You’ll help us expand detection and mitigation methods against abuse across all audio verticals on our platform. The team’s goal is to ensure a fraud-free experience for users and creators by employing advanced technology and evolving strategies to maintain fair engagement and accuracy.

As part of the team, you’ll contribute to our data-driven approach, protecting the platform's integrity from issues like account abuse and artificial manipulation. Your work will directly impact how billions of fans connect with millions of artists and creators, and how the world experiences content.

You’ll work with a team of data scientists and machine learning engineers to detect and prevent abuse on our platform. You’ll help us investigate anomalous trends, discover new ways to leverage data for improved detection methods, and identify unwanted behavior on the platform. We are a fast-paced team passionate about high-impact projects, and we prioritize continuous learning and skill development. You will have the freedom to refine your skills and working methods.

What You'll Do

    • Investigate evolving fraud trends and consumption habits to enhance detection capabilities.
    • Apply your expertise in quantitative analysis, data mining, and data presentation to help automate, optimize and understand key business problems and solutions.
    • Build data and tooling to empower operational and exploratory data analysis while optimizing for speed, accuracy, and quality.
    • Work closely with cross-functional teams of data and backend engineers, and product managers.
    • Partner with a broad range of stakeholders across music, podcasts and audiobooks to consistently uphold platform integrity.

Who You Are

    • A Bachelor's degree in Data Science, CS, or another quantitative field.
    • 4+ years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines.
    • Deep understanding of data with expertise in data manipulation and design (SQL) and experience in Python.
    • 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.
    • A continuous learner, excited by new technologies and able to pick up new tools and frameworks quickly.

Where You'll Be

    • This role is based in Toronto.
    • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. 
Spotify is an equal opportunity employer. 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.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

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.