Abuse Investigator Jobs

Who we are About the team The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns 10+ real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates directly into dollar impact for Stripe and its users. The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. Radar is growing fast, and the team is actively building new products like defenses against AI token theft, free trial abuse, and programmatic attacks. What you'll do In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch. Responsibilities Design, build, train, evaluate, deploy, and own ML models in production that detect fraud across Stripe’s global payments network Design and build large-scale ML systems that operate on diverse and large scale data Experiment and iterate on ML models to achieve key business goals around data quality and accuracy Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliability Collaborate with product, data science, and engineering partners across Stripe to identify opportunities where ML can improve outcomes for merchants and consumers Engage with the latest ML/AI developments and take calculated risks in transforming innovative ideas into productionized solutions Mentor engineers and contribute to a strong ML engineering culture within the team Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are enco

The Loyalty Analyst helps run and continuously improve our loyalty program, owning its day-to-day administration while digging into what drives members to visit more often and spend more per visit. This person also safeguards the program's integrity by identifying and stopping fraudulent or abusive activity before it erodes program value. Working closely with marketing, finance, and technology teams, the Loyalty Analyst ensures the program runs smoothly and delivers real return on investment and serves as the primary point of contact for our loyalty vendor. Administer the day-to-day operations of the loyalty program, including point accrual and redemption rules, tier logic, and member account maintenance. Analyze loyalty member behavior to identify opportunities that increase return visit frequency and average guest check Monitor program transactions for signs of fraud or abuse (e.g., point gaming, account sharing, redemption anomalies) and escalate or resolve issues as needed. Build reporting and dashboards to track core loyalty KPIs: enrollment, active member rate, redemption rate, breakage, and member lifetime value. Partner with marketing to design and evaluate targeted offers, promotions, and campaigns aimed at loyalty members Work with technology and vendor partners to troubleshoot loyalty platform issues and support enhancements. BENEFITS Free Play & 1/2 price food! Health, dental, vision, 401(k) team member match, free mental well-being platform – and that’s just for starters for those who qualify. View team member benefits here. <p style="text-align:left !importan

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: We are seeking a skilled and innovative Application Security Engineer to join 𝕏 Money. In this role, you will protect the security and integrity of our payments and financial products throughout the software development lifecycle, with a particular focus on code security, CI/CD pipelines, and systems that move and hold customer funds. Experience securing fintech, payments, digital wallet, ledger, or similar high-value platforms, where fraud, abuse, and unauthorized transfers are a constant concern, is strongly preferred. RESPONSIBILITIES: Conduct in-depth code reviews and static analysis to identify and mitigate security vulnerabilities in financial applications Design and implement secure coding guidelines and best practices for development teams Collaborate closely with development teams to integrate security practices throughout the CI/CD pipeline Perform threat modeling and risk assessments for payments, wallets, ledgers, and related product surfaces, and develop mitigation strategies for fraud, abuse, and unauthorized movement of funds or credits Manage vulnerability tracking and remediation efforts, providing guidance to development teams Manage the

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. The head of EMEA Refund Fraud will lead Doordash’s EMEA strategy for preventing and managing refund abuse across our marketplace. You will be accountable for the performance of the Credit and Refund (C&R) Fraud domain: setting the long-term vision, determining where we focus our resources, and building the team, controls and capabilities required to reduce fraud sustainably while protecting the experience of genuine customers. This is a senior leadership role at the intersection of Integrity, Customer Care, Product, Engineering, Analytics and Finance. You will lead a team of experienced fraud and strategy professionals and work with senior leaders across Deliveroo to make complex decisions about fraud risk, customer experience, operational cost and product investment. You will need to be comfortable operating in ambiguity, identifying problems before they become material, and turning complex and sometimes incomplete signals into a clear strategy. Success will come not from personally solving every problem, but from creating the direction, operating mechanisms and team that enable Deliveroo to manage refund fraud effectively at scale. What You’ll Be Doing Setting the C&R Fraud Strategy Set and own the 1–2 year vision and strategy for C&R Fraud, translating wider Integrity and business priorities into a focused roadmap. Proactively identify emerging risks, systemic vulnerabilities and opportunities rather than waiting for problems to be assigned. Determine the highest-value problems for the team to solve and make clear choices about where we should (and should not) invest. Define how we balance fraud loss, customer experience, operational cost and growth when desig

About the Team At Trendyol Finance, we drive financial clarity, sustainability, and smart decision-making at every level of the business. As a strategic partner to commercial teams, we bridge data with action—ensuring efficiency, compliance, and long-term value creation. From budgeting to forecasting, we turn numbers into insights that shape Trendyol’s growth journey in a fast-moving ecosystem. About the Role We are seeking analytical, process-oriented and proactive Fraud Process & Analytics Professionals to join our Fraud team. This role sits at the intersection of fraud domain knowledge, data analysis, process design and project delivery. You will identify fraud and abuse risks, translate business problems into analytical questions, use data to quantify root causes and impact, design scalable controls and rulesets, and drive improvements together with Product, Data, Tech, Operations and Business teams. The role is not limited to reviewing individual cases; the main focus is to turn recurring fraud problems into measurable, scalable and sustainable solutions. Your Main Responsibilities Own and improve fraud-related processes end-to-end by identifying control gaps, bottlenecks, manual steps and potential abuse points, and drive scalable improvements through automation, product changes or operational redesign. Analyze customer, seller, order, payment and behavioral data using SQL / BigQuery to identify fraud patterns, anomalies, root causes and emerging risk signals; structure ambiguous problems into clear hypotheses, populations and success metrics. Quantify the financial, operational and customer/seller experience impact of fraud problems, prioritize initiatives accordingly, and translate analytical findings into actionable recommendations. Design and improve fraud rulesets, risk indicators, thresholds, controls and monitoring frameworks, considering false positive / false negative trade-offs and overall control effectiveness.

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Your job is to make sure every payout and transaction lands with the right person. We have spent years getting very good at protecting the things a marketplace has always had to protect: checkout fraud, account takeover, courier abuse. But we are no longer only a marketplace. We now issue banking products, lend to merchants, move instant payouts to couriers, and collect cash on the doorstep. Every one of those is a new way for money to leave the platform. This is a new team, and it owns that surface: fraud wherever money moves through the platform. Who receives it, who lends it, who collects it, and who holds it in a financial account. Think instant payout rails, merchant cash advances, and platform-issued banking and earned-wage products serving millions of couriers and merchants. These are live loss surfaces, and the volume grows with every financial product we launch. We are now looking for a Backend Engineer (Golang) to build that protection. You will design and ship real-time detection and automated enforcement for our financial products across DoorDash, Wolt, and Deliveroo. The work is high-throughput, low-latency, and unusually consequential: a rule you ship on Monday can stop a serious loss by Friday. It is also close to greenfield, so you will be setting the patterns every future financial product inherits on day one. This role will be based in London , UK as one of the founding engineering roles in our London hub, working closely with our teams in Helsinki and Berlin. What you'll do: Build and maintain high-throughput, low-latency backend services in Go that score financial events in real time, including payout enrollments, bank account links, credit applications,

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Waste & Error Certified Coding Manager is responsible for leading the Certified Coding Analyst and W&E Team Lead roles that conduct medical claim reviews and coding audits to identify billing errors, waste, abuse, fraud, and payment integrity opportunities. The Manager provides direct people leadership, establishes operational priorities, ensures consistent application of coding and billing requirements, and is accountable for team productivity, quality, service levels, compliance, and employee development. This role partners closely with the W&E team lead, who provides day-to-day technical guidance and subject matter support to the coding team. The Manager retains accountability for staffing, performance management, workload oversight, escalations, audit readiness, process improvement, and delivery of business outcomes. The position also represents the team in discussions with senior leadership, Medical Directors, Legal, Compliance, Analytics, Operations, and other Payment Integrity partners. Primary Responsibilities People Leadership & Team Development Lead, coach, and develop a team of Certified Coding Analysts and Senior Certified Coding Analysts. Establish clear role expectations, performance goals, productivity standards, quality requirements, and accountability measures. Conduct regular perfor

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Link is a digital wallet designed for fast and secure online payments. It allows consumers to save and use their preferred payment methods across the Link network, helping them check out quickly and securely wherever Link is accepted. The Link Fraud and Auth team works to make Link the most trusted and highest-performing way to pay. We protect consumers and merchants from fraud, abuse, and financial loss while maximizing authorization rates for good users. Our work spans consumer-facing experiences, payment infrastructure, and ML powered risk systems. We manage fraud and financial risk across a growing range of novel Link features, including Link’s agentic wallet, stored balance, and LPMs. The team also owns Instant Bank Payments, a proprietary payment method built on ACH rails, offering merchants immediate confirmation while protecting them from bank-initiated returns. IBP is the heart of Link’s revenue engine, giving LFA engineers the opportunity to shape and scale one of Link’s most important products. What you’ll do As a machine learning engineer on Link Fraud and Auth, you’ll build and operate models and risk decisioning systems that protect Link while helping more legitimate payments succeed. You’ll work across the full machine learning lifecycle, from analyzing fraud patterns and identifying opportunities to building, deploying, monitoring, and improving models in production. You’ll use data to form hypotheses, make practical modeling

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. About the Role Hybrid (3 days per week in the London office required) Individual contributor role Every day, millions of customer transactions flow through our platform. Our challenge is to make payments effortless for genuine customers while preventing fraud, abuse, and financial loss. As the Senior Strategy & Operations Manager for Payments Risk & Fraud, you'll own one of our most commercially important problem spaces. You'll define the strategy for payment fraud, promotions abuse, cash risk, and chargebacks – balancing customer experience, growth, and profitability. This is an end-to-end ownership role. You'll identify opportunities, shape strategy, influence product and engineering roadmaps, partner with data science to improve detection models, and work closely with Finance and Payments to protect revenue while enabling sustainable growth. If you enjoy solving ambiguous, high-impact business problems using data, technology, and cross-functional leadership, we'd love to hear from you. What You'll Own Defining our Payments Risk Strategy Own the strategy and roadmap for payment fraud, promotions abuse, cash risk, and disputes across multiple markets. Identify emerging risks, prioritise investments, and continuously evolve our controls to protect customers and the business while supporting growth. Driving Commercial Performance: Own the key business metrics that matter, including: Fraud losses Chargeback rates Payment approval rates Promotions efficiency Recovery rates False positive rates Evaluate trade-offs between risk, customer experience, and conversion to maximise long-term profitability Building Data-Driven Solutions Use data to understan

Adobe is seeking a Machine Learning Engineer to join the Adobe Risk Platform (ARP) team. ARP is Adobe's centralized, adaptive system for detecting, preventing, and mitigating fraud and abuse across products and services — protecting surfaces like Commerce, Stock, and Firefly with real-time risk decisions, without degrading the customer experience. In this position, you will help build and develop machine learning models to identify fraudulent activity, detect abusive account behavior, and protect the experience of hundreds of millions of users. You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team. Key Responsibilities Help build and train ML models covering various fraud and abuse areas. These include financial transaction fraud, device-related deception, and account and identity abuse. The goal is a unified, continuously-updated trust and risk score. Contribute to feature engineering across transaction, device, and behavioral event data. Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs. Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability. Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams to understand fraud and abuse patterns across Adobe's surfaces. Stay ahead of advances in ML/AI, particularly in fraud detection and behavioral modeling, and bring relevant ideas to the team. Minimum Qualifications Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience). 3

Adobe is seeking a Machine Learning Engineer to join the Adobe Risk Platform (ARP) team. ARP is Adobe's centralized, adaptive system for detecting, preventing, and mitigating fraud and abuse across products and services — protecting surfaces like Commerce, Stock, and Firefly with real-time risk decisions, without degrading the customer experience. In this position, you will help build and develop machine learning models to identify fraudulent activity, detect abusive account behavior, and protect the experience of hundreds of millions of users. You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team. Key Responsibilities Help build and train ML models covering various fraud and abuse areas. These include financial transaction fraud, device-related deception, and account and identity abuse. The goal is a unified, continuously-updated trust and risk score. Contribute to feature engineering across transaction, device, and behavioral event data. Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs. Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability. Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams to understand fraud and abuse patterns across Adobe's surfaces. Stay ahead of advances in ML/AI, particularly in fraud detection and behavioral modeling, and bring relevant ideas to the team. Minimum Qualifications Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience). 5

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The InfoSec team protects Affirm’s systems and data from evolving threats. We manage security risk, monitor vulnerabilities, and enforce protective controls across the company. The team leads incident response, compliance, identity and access management, and employee training. Our goal is to ensure that security is built into every system and decision at Affirm. We maintain a secure, trustworthy environment so the business can operate and grow with confidence. In this role, you'll build and run Affirm's end-to-end security review process for enterprise AI/LLM systems evaluating architecture, prioritizing AI-specific risks, and designing the controls and guardrails that let Affirm adopt AI safely, partnering across Security, Legal, Privacy, Compliance, IT, and Engineering to make it scalable and repeatable. What you’ll do You will lead and continuously improve Affirm's enterprise AI security review process evaluating the architecture, data flows, permissions, and design of internal AI tools, agentic/MCP-based systems, and AI features — and embed security requirements into the design phase. You will threat model AI/LLM-based systems and their data flows for risks such as prompt injection, insecure output handling, excessive agency, tool-permission abuse, data poisoning, and sensitive-data exposure, and drive remediation. You will review source code, system prompts, agent configurations, and tool/permission manifests (e.g., MCP definitions), and help tool owners build security-focused test cases and red-team/eval scenarios to verify requirements before launch. You will design and build security guardrails and tooling for AI systems permission boundaries, authn/authz for agentic tools and MCP servers, data-handling controls, logging/monitoring, and policy-as-code (Python, IaC) — to enforc

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The InfoSec team protects Affirm’s systems and data from evolving threats. We manage security risk, monitor vulnerabilities, and enforce protective controls across the company. The team leads incident response, compliance, identity and access management, and employee training. Our goal is to ensure that security is built into every system and decision at Affirm. We maintain a secure, trustworthy environment so the business can operate and grow with confidence. In this role, you'll build and run Affirm's end-to-end security review process for enterprise AI/LLM systems evaluating architecture, prioritizing AI-specific risks, and designing the controls and guardrails that let Affirm adopt AI safely, partnering across Security, Legal, Privacy, Compliance, IT, and Engineering to make it scalable and repeatable. What you’ll do You will lead and continuously improve Affirm's enterprise AI security review process evaluating the architecture, data flows, permissions, and design of internal AI tools, agentic/MCP-based systems, and AI features — and embed security requirements into the design phase. You will threat model AI/LLM-based systems and their data flows for risks such as prompt injection, insecure output handling, excessive agency, tool-permission abuse, data poisoning, and sensitive-data exposure, and drive remediation. You will review source code, system prompts, agent configurations, and tool/permission manifests (e.g., MCP definitions), and help tool owners build security-focused test cases and red-team/eval scenarios to verify requirements before launch. You will design and build security guardrails and tooling for AI systems permission boundaries, authn/authz for agentic tools and MCP servers, data-handling controls, logging/monitoring, and policy-as-code (Python, IaC) — to enforc

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Software Engineer for our Anti-Abuse team within Security Foundations. This team is responsible for protecting Snowflake and our customers from abuse on the Snowflake platform — building foundational security primitives across a complex multi-cloud environment to combat fraud, account takeovers, data exfiltration, and AI security threats at the scale of Snowflake’s hyper-growth. AS A SENIOR SOFTWARE ENGINEER, SECURITY FOUNDATIONS AT SNOWFLAKE, YOU WILL: Design, build, and scale security-by-default capabilities that protect Snowflake products across a complex multi-cloud environment Develop intelligent security platforms and services that leverage AI/ML and risk scoring to identify, prioritize, and respond to security threats and policy violations Build real-time detection and prevention systems to defend against account compromise, AI abuse, and data exfiltration through adaptive enforcement and granular policy controls Create security intelligence and monitoring capabilities that detect suspicious account & user activity, generate actionable insights, and enable timely response Partner across Security, Engineering, and Product teams to define security strategy, influence product design, and drive adoption of secure engineering practices Raise the

Non-Financial Risk (Enterprise Risk) Consultant – All Levels Location: Glasgow & Edinburgh (Hybrid) | Practice Area: Finance, Risk, Regulatory & Financial Crime | Type: Permanent Drive impactful change across enterprise risk, market abuse, and surveillance frameworks The Role Capco is looking for Management Consultants with expertise in Non-Financial Risk to join our growing Finance, Risk, Regulatory & Financial Crime (FRRF) capability. You'll work on a variety of projects for leading financial institutions, delivering risk transformation and advisory services across enterprise and operational risk. Acting as a trusted advisor, you'll help shape the future of risk frameworks, controls, governance, and surveillance capabilities. You'll also embrace AI-enabled ways of working, using approved AI tools to enhance analysis, improve delivery efficiency, and support better decision-making while applying appropriate human judgement and responsible AI practices. What You'll Do Support enterprise and operational risk transformation projects, leveraging AI-enabled analysis where appropriate to improve delivery, insight, and operational effectiveness. Document, assess, and enhance risk processes and controls across the first and second lines of defence, identifying opportunities for automation and AI-enabled workflow improvements. Contribute to market abuse and trade surveillance initiatives by reviewing controls, detection scenarios, and the responsible application of AI to improve surveillance effectiveness and reduce false positives. Support AI model tuning and optimisation activities within surveillance environments, ensuring appropriate governance, validation, auditability, and human oversight. Engage stakeholders across business, technology, compliance, and risk functions to deliver collaborative, data-driven transformation initiatives. What We're Looking For Experience in enterprise or operational risk, ideally within financial services or management c