Sr. Fraud Analyst

Mode

We are looking for a Senior Fraud Analyst to join our Customer Success team and protect the Mode Mobile ecosystem from fraud and abuse. In a rewarded app, users earn real money and rewards, so every fraudulent account costs us directly: rewards paid to users who did not earn them, partner reversals, wasted acquisition spend, and a worse experience for the real users who earn with us. How well we stop fraud affects our margins, our relationships with advertising and offer partners, and the trust of our community, which makes this one of the highest-impact roles on the team.

You will review our fraud data, investigate accounts to decide whether they are fraudulent, analyze Mobile Measurement Partner (MMP) and partner network data to find invalid and fraudulent traffic, and track fraud trends across our rewarded apps, with a primary focus on the Mode Earn App and EarnWise. Fraud in this space changes fast: multi-accounting, device farms, emulators, VPN and proxy abuse, bots and AI-driven automation, shared payout accounts, and offer manipulation all show up in rewarded apps. You will stay ahead of them by turning what you learn into rules, safeguards, and recommendations that stop fraudulent users while keeping the experience smooth for legitimate ones.

You will work closely with Customer Support, Product, Engineering, Growth, and our partners, and you will be the team's expert on fraud. You will set review standards, mentor teammates, and report to leadership on fraud losses, trends, and results. We are looking for someone who is comfortable owning decisions, working with incomplete data, and measuring the impact of their work.

Our AI-Native Team

Our Customer Success team, which includes Fraud, is AI native. We use AI in our daily work to summarize account histories, analyze large data exports, find patterns across large sets of accounts and events, draft case notes and reports, and speed up routine reviews. This lets us cover more ground than manual review alone, so analysts can spend their time on the hardest cases and on building better defenses. Analysts make every final decision on whether an account is fraud and review AI-assisted findings before acting on them. As a senior member of the team, you will help define how to apply AI to our fraud workflows and how we keep it accurate and safe.

You do not need any experience with AI. A willingness to learn is a requirement: we expect everyone on the team to learn our AI tools and workflows, try new approaches, share what works, and say so when something does not. We will teach you the tools we use and how we use them.

Who You Are and What You'll Do

• Review our fraud data across the rewarded apps every day to monitor user behavior, earnings, and cash-out activity, and to find the users and patterns that put our ecosystem at risk
• Investigate accounts and decide whether each is fraudulent, using device, network, identity, linked account, payment, and behavioral data, and document your reasoning so decisions are consistent and can be defended
• Review redemptions and payout requests for warning signs such as shared payout accounts, clustered cash-outs, and unusual velocity, stop fraudulent payouts, and make sure legitimate ones are processed in a timely manner
• Analyze MMP and partner network data, such as installs, attribution, click-to-install time, conversion and postback data, and post-install events, to identify invalid traffic, bots, install farms, and fraudulent sources, and recommend action on the affected partners, campaigns, and offers
• Work with the Growth team and our partners to dispute invalid conversions, support reversal and refund discussions with clear evidence, and remove traffic sources that bring in fraud
• Identify and track fraud trends and new fraud tactics across our apps, forecast what they mean for future risk and cost, and share clear recommendations with the team and leadership
• Build and refine the rules, risk scores, thresholds, and step-up verification, such as one-time passcodes and identity checks, that we use to flag, challenge, and block users, test changes before they go live, and measure accuracy, including false positives that affect legitimate users
• Partner with Product, Engineering, and Growth to turn fraud findings into product changes, controls, and safeguards that protect the ecosystem, and write clear requirements for the data and tools you need
• Build dashboards, queries, and reports in our analytics and BI tools that quantify the financial impact of fraud, including rewards paid out, partner reversals, and effects on gross margin, and provide daily, weekly, and monthly reports on key metrics such as fraud rate, accounts actioned, payouts prevented, and false positive rate
• Stay up to date on fraud research, industry news, new tools, and the tactics fraudsters use against rewarded apps, and bring what you learn back to the team
• Partner with Customer Support to handle escalations and appeals from users who dispute fraud decisions, and make sure legitimate users are treated fairly and quickly
• Set review standards, train and mentor Customer Support team members and other analysts on fraud indicators, escalation paths, and case documentation, QA fraud-related decisions, and keep our fraud playbooks current
• Evaluate our fraud vendors and tools, including how well they perform, what they cost, and where the gaps are, and recommend changes
• Use AI tools in your daily work, such as analyzing data exports, summarizing account histories, finding patterns, and drafting case notes, and review all AI-assisted work for accuracy before you act on it
• Share what you learn about AI tools and workflows with the team, and suggest ways to improve how we use them
• Maintain confidentiality of user information and our fraud detection methods, and perform other duties as the need arises

What You Bring to the Team

• You have 4+ years of experience in fraud analysis, trust and safety, risk, or a related analytical role, including hands-on experience investigating accounts and deciding whether they are fraudulent, preferably in rewarded apps, offerwalls, mobile gaming, fintech, or ad tech.
• You can show a track record of finding fraud patterns, building the rules or controls that stop them, and measuring the results.
• You have a strong analytical mindset, are proficient in SQL and spreadsheets, and can break down large data sets on your own to find relationships, gaps, and patterns and explain what they mean for the business. Experience with analytics tools such as Mixpanel and Google Analytics is expected, and Python is a plus.
• You understand how fraud works in rewarded and incentive-based apps, including multi-accounting, device farms, emulators and device spoofing, VPN and residential proxy abuse, bots and AI-driven automation, shared payout accounts, and offer and referral abuse.
• You have experience analyzing Mobile Measurement Partner (MMP) data from platforms such as Singular, AppsFlyer, or Adjust, and you understand how install and attribution fraud works, including click flooding, click injection, install hijacking, SDK spoofing, and device ID resets.
• You understand how offerwalls and performance partner networks work, including conversions, postbacks, and reversals.
• You have sound judgment, own high-stakes decisions, and make accurate calls with incomplete information, balancing fraud prevention with a good experience for legitimate users.
• You have o