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Spotify

Fraud Analyst (Revenue Protection) - 12-Month Fixed-Term

London
Posted 1 day ago
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Are you passionate about combating fraud, safeguarding revenue, and protecting users from sophisticated threats?

As Spotify continues to grow and innovate, we are looking for a dedicated Fraud Analyst to join our Revenue Protection Operations team. In this role, you will play a crucial role in enhancing our fraud prevention strategy—ensuring a proactive balance between user growth, revenue protection, and maintaining a safe, scalable platform.

With scale comes complexity. You will focus on tackling payment fraud, chargebacks/disputes, creator onboarding, and platform misuse that risks revenue leakage and partner trust.

As a 12-month cover, you will seamlessly step into our ongoing operations, keeping our momentum strong while bringing fresh perspectives to our workflows. You will work with a global team of world-class business managers, data scientists, product managers, and engineers to build robust operational defenses. If you have a keen eye for detail, strong analytical skills, and a drive to stay one step ahead of fraudsters using cutting-edge technologies, we want to hear from you!

What You’ll Do

  • Detection & Mitigation: Review suspicious activity flagged by our fraud systems and take swift mitigating and preventative action to protect our genuine users, secure our growth, and minimize revenue leakage.
  • AI & Tooling Innovation: Actively utilize, test, and adopt emerging AI technologies and automated tooling to enhance fraud detection and improve operational productivity.
  • Build & Optimize: Partner closely with internal Product and Engineering teams as well as external vendors to help contribute to the design, requirement gathering, and testing of tooling and system changes to capture evolving fraud and abuse trends early.
  • Trend Analysis & Investigation: Be creative and proactively seek out new fraud and misuse trends. Present data-informed findings and retrospectives to suggest robust performance guardrails.
  • Cross-Functional Collaboration: Handle daily fraud and misuse escalations while working closely with Data Science, Engineering, and Product teams to translate operational insights into risk mitigation frameworks.
  • Operational Excellence: Support the Revenue Protection leadership in maintaining and improving internal policies, process automation, evidence handling, and operational playbooks.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Who You Are

  • Experience: 2+ years of experience in a fraud analyst or revenue protection role, preferably within an e-commerce, merchant fraud, or creator & marketplace platform environment. Given the fixed-term nature of this role, the ability to rapidly adapt and hit the ground running is highly valued.
  • Domain Knowledge: Familiarity with common fraud prevention techniques, dispute/chargeback management, financial crime risks, and emerging industry trends.
  • AI & Systems Mindset: Direct experience working with machine learning and rule-based fraud prevention tooling (such as Ravelin, Sift, Signifyd, Accertify, etc.). You possess the confidence and curiosity to leverage AI technologies to test, scale, and optimize internal fraud detection tools.
  • Data Proficiency: Strong data analysis skills using SQL (knowledge of Google BigQuery is a plus) and experience with dashboard visualization tools like Looker, Tableau, or similar.
  • Analytical Thinker: An ambitious and creative problem solver who works well independently, thrives when handling ambiguity, and can break down complex technical risks into practical applications.
  • Collaborator & Communicator: A highly communicative person with a collaborative mindset who excels at building strong relationships with internal stakeholders, operations, and global partners.

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Where You’ll Be

You'll be based in London, UK. We offer you the flexibility to work where you work best! There will be some in-person meetings, but it 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice

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Skills

Fraud Detection
Revenue Protection
SQL
Data Analysis
Chargeback Management
Machine Learning Tooling
Trend Analysis
Cross-Functional Collaboration
Risk Mitigation
Google BigQuery
Looker
Tableau

Location

London, England, United Kingdom

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