Abuse Research Engineer Jobs

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

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 Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world. What you’ll do In this role, you will play a critical part in safeguarding our financial ecosystem through two main pillars: actively responding to live fraud and abuse incidents as a hands-on security engineer, and serving as a key bridge between incidents and merchants to help them remediate threats, improve security posture, and protect their accounts. Leveraging your technical depth in fraud, abuse, and security engineering, you will investigate high-risk accounts, perform post-incident analyses, gather operational requirements, and drive agentic response capabilities ensuring we neutralize threats with speed and precision while elevating Stripe's product integrity function. Responsibilities Respond to live fraud and abuse incidents as a Forward Deployed Security Engineer, investigating high-risk activity, neu

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

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Lead on the User Well-Being team, you will be responsible for managing our child safety, mental health, abuse and exploitation, and age assurance enforcement workflows. This will include managing the team responsible for scaling, maintaining, and continuously improving the systems and processes we use to detect and respond to these harms. This is a management role. You will serve as the central point of contact for those who conduct content review, managing day-to-day workflows, quality assurance, and escalation processes. You will also work closely with internal Engineering, Policy, and Legal teams to scale detection systems and close enforcement gaps as the threat landscape evolves. Important context for this role: In this position you will regularly be exposed to and engage with explicit content of a sexual nature involving minors, as well as content that may be violent or psychologically disturbing. Anthropic takes the wellbeing of team members working in this area seriously and provides access to wellness resources and support. Candidates should carefully consider this aspect of the role before applying. Key responsibilities Manage a team of individual contributors across multiple policy areas under the User Well-Being banner Serve as the primary point of contact for review partners conducting content review, including onboarding, training, quality assurance, and ongoing relationship management Design and improve enforcement workflows to scale effectively as volume grows, while maintaining high accuracy and consistency across review decisions Partner with Engineering and Data Science tea

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 Payment Intelligence is comprised of multiple product teams building AI-first solutions to some of our customers’ biggest challenges, including fraud/abuse ( Radar ), payment optimizations ( AuthBoost ), Disputes, Authentication, and merchant analytics. We’re a mix of machine engineering engineers and full-stack software engineers impacting ~every Stripe transaction, creating revenue opportunities for Stripe and our customers, and helping protect the broader ecosystem. We have the benefit and privilege of working on cutting edge technologies with incredible scale and reach while also working directly with our merchants every day to build the right products for their needs. What you'll do As a Staff Engineer on Payment Intelligence, you’ll work across our product portfolio to ensure we’re building in a consistent, efficient, and effective manner. Experience with large, distributed systems on the critical path will help candidates succeed, as will comfort working across the stack and interacting with ML teams and models. Responsibilities Define technical strategy for multiple experiences across the Payment Intelligence portfolio, with a focus on quality and performance Champion a quality-first engineering culture - establish standards, tooling, and processes that make it easy to ship high-quality code at scale Partner with some of Stripe’s largest merchants to co-build the future of payment-centric intelligence Partner cross-functionally