Fraud Operations Analyst Jobs

Integra’s mission is to restore integrity to the financial system. Integra is looking for a business development research intern to partner with the business development team to seek out legal cases pertaining to complex financial fraud in order to craft outreach to legal entities involved in those cases. Responsibilities would include the following: Aggregating weekly prospecting targets for email campaigns Identifying potential new matters for outreach Updating and maintaining Integra’s CRM Identifying speaking engagements and conferences Managing content calendar for LinkedIn postings Controlling quality, design, and additions to Integra sites Other activities to support Integra’s Business Development and Marketing efforts Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Integra’s mission is to restore integrity to the financial system. Integra is looking for a research analyst to partner with quantitative analysts to develop and enhance existing methods for investigating fraud. This person will conduct research on a variety of topics related to fraud. Responsibilities would include the following: Reviewing academic research and news articles related to financial, securities, cryptocurrency or health care fraud Identifying emerging areas of fraud based on review of news, social media and other sources Reviewing specific cases of fraud, including analysis of specific organizations, entities or institutions Gathering of publicly available data and information Compiling and summarizing research Other tasks to support Integra’s business Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Integra’s mission is to restore integrity to the financial system. Integra is looking for a business development research intern to partner with the business development team to seek out legal cases pertaining to complex financial fraud in order to craft outreach to legal entities involved in those cases. Responsibilities would include the following: Aggregating weekly prospecting targets for email campaigns Identifying potential new matters for outreach Updating and maintaining Integra’s CRM Identifying speaking engagements and conferences Managing content calendar for LinkedIn postings Controlling quality, design, and additions to Integra sites Other activities to support Integra’s Business Development and Marketing efforts Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Data Scientist Lead Location: Hong Kong (Hybrid) | Practice Area : Data & Analytics | Type: Permanent The Role As a Data Scientist Lead at Capco, you’ll help clients optimise fraud models, machine learning platforms and supporting Google Cloud infrastructure, turning detailed analysis into practical, implementation-ready recommendations. You’ll take a hands-on approach to improving model and platform performance, reliability and run-cost across GCP infrastructure and ML pipelines. Working closely with IT infrastructure teams, data scientists and fraud stakeholders, you’ll identify opportunities to reduce compute and inference costs while maintaining effective, resilient solutions. You’ll provide configuration-level and code-level guidance, supported by clear estimates of implementation effort, expected savings and measurable outcomes. You’ll also use approved AI tools and AI-enabled workflows where appropriate to accelerate analysis, improve insight and support delivery, while maintaining human judgement, appropriate review and responsible AI guardrails. What You’ll Do GCP engineering: Lead hands-on design, diagnostics and optimisation across compute, storage and network services, implementing monitoring and observability to improve cost, performance and reliability. Fraud ML modelling: Support the development, validation and deployment of fraud and ML models end-to-end, identifying measurable opportunities to reduce compute requirements, accelerate inference and improve automation. ML and data pipelines: Optimise pipelines spanning ingest, transformation, feature creation and serving, training and inference, with a focus on cost efficiency, performance, resilience and responsible AI-enabled automation where appropriate. Big data and distributed processing: Develop and tune large-scale batch and streaming workloads using Spark or similar technologies, improving efficiency, stability and production readiness. Engineering excellence: Apply strong Python and SQL sk

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers. WHY AUTHENTICATION & SECURITY? Authentication & Security sits at the intersection of trust, product, and growth. The team builds the systems that allow users to sign in, recover, and protect their accounts with confidence, while defending the platform against account takeovers, credential abuse, and fraud at massive scale. This role is an opportunity to shape a high-stakes product area where small changes in friction or protection can meaningfully affect sign-ups and user frequency. You will act as a strategic leade

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. Realizing that vision requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build Replit's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and decisions that protect Replit's users, platform, and economics. You'll work closely with Engineering, Support, Legal, Security, Infrastructure, Money, and Growth to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse rate to understand selection effects, missing labels, policy changes, attacker adaptation, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and outcomes are high stakes. Ground truth is delayed, biased, and often incomple

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior ML Engineer, you'll play a central role in building the data science behind the products — from framing new fraud, risk, and intelligence problems, to designing and deploying ML models at scale, to helping our enterprise customers and go-to-market teams understand and act on the insights we generate. What you’ll do: Design, build, and continuously improve the ML models that power our risk and intelligence products, and take ownership of new signals as they get scoped. Take a loosely defined business or customer problem and break it into a clear data problem, articulating value, impact, and complexity before proposing a solution. Build anomaly detection, fraud, and risk-modeling approaches — including network/graph-based methods — that keep our signals accurate and resistant to adversarial behaviour. Own model development, deployment, and monitoring end-to-end, partnering with ML/data engineers on scalability, reliability, cost, and dashboards/alerting. Design and run experiments (A/B tests, offline customer POCs) to validate new signals before they roll into production. Manage and analyse large, multi-country datasets, ensuring data integr

About the role There’s a wide gap between an agent that works in a demo and one that works across millions of live transactions. Closing it is the job. You’ll embed with the teams and customers who depend on AI — risk, fraud, collections, payments, support, developer experience — and design, build, and ship agentic systems into their production environments. You’ll also help build the platform underneath: Paytm’s AI inference platform (Pi) and the agentic runtime, orchestration, and tooling that lets agents reason, plan, use tools, and run multi-step workflows safely. What you’ll do Embed & deploy Tackle greenfield problems alongside internal teams and customers — scope ambiguous needs and build agents from scratch that fit how they actually work. Own deployments end-to-end: discovery, build, integration, activation, and the tuning that earns trust and adoption. Lead pilots and demos, drive adoption, and clear blockers before they stall a rollout. Build agentic systems Architect agentic systems — reasoning, planning, tool use, memory, multi-agent coordination — that run real workflows with guardrails. Build safe tool-use infrastructure across APIs, databases, and services, with permissioning, sandboxing, and human-in-the-loop. Ship SDKs, patterns, and reusable blueprints so internal teams build and deploy agents fast. Make it reliable Design and run rigorous evals: measure quality, catch regressions, and feed results back into the system. Build observability, tracing, and guardrails that prove agents are safe and keep them safe as models and data drift. Own the multi-model inference your agents depend on (text, voice, code, vision) — latency, throughput, and cost. Lead Set technical direction and standards for agentic systems; mentor engineers and partn

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're hiring a hands-on Engineering Manager to build and lead Replit's Anti-Abuse team from the ground up. This is a foundational 0-to-1 role: you'll define the anti-abuse roadmap, hire a small team of engineers and data analysts, and ship the systems that protect Replit's platform, users, and economics from adversarial actors. You'll partner across Support, Legal, Security, Infrastructure, and the Money and Growth teams to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, and increasingly, abuse driven by AI agents themselves. The team you build will define how Replit defends against all of it. What You'll Do Build the anti-abuse roadmap from scratch : Define the threat model, prioritize across abuse vectors (phishing/scam hosting, cryptomining, token farming, payment fraud, AI agent exploitation), and translate it into a shipping plan with clear sequencing and tradeoffs. Design progressive verification and identity infrastructure : Build the "ladder of trust" that gates increasing platform capabilities (referrals, additional credits, access to powerful agent features, Missions) behind escalating verification. This includes a humanity/identity layer that's distinct from user accounts, integrations with KYC-grade verification providers, and the policy engine that decides what level of trust unlocks what behavior. This infrastructure is core not just to promo integrity but to how Replit safely expands agent capabilities over time. Ship as a hands-on EM : Stay in the code. Use the latest AI coding tools (including Rep

Integra FEC (Financial Economic Consulting) is a litigation and economic consulting firm that exists to restore integrity to the financial system through forensic data analytics. We work with government agencies and law firms in their efforts to combat a wide array of financial fraud, in areas ranging from securities to healthcare to crypto assets. We are looking for strong candidates with quantitative and financial backgrounds and a natural curiosity to learn to join our team and help tackle complex projects by efficiently analyzing data. Main responsibilities include: Plan, develop, and take ownership in data-intensive investigations related to financial fraud Write scripts to retrieve and organize data; parse free-form text fields, images, and spreadsheets to derive insights Construct and analyze large datasets to find fraudulent patterns; develop quantitative and empirical methods to analyze potentially fraudulent conduct Summarize and present findings to technical and non-technical audiences, through long-form reports, charts and slides Anticipated to grow toward managing projects and communicating with clients Job Qualifications Required 3+ years of relevant work experience Background in statistics, mathematics, engineering, computer science, data science, accounting, finance, economics, or other quantitative field Demonstrated experience with R, Python, and/or SQL Attention to detail Intellectual curiosity and interest in fraud analysis Highest ethical standards Strong teamwork abilities Preferred Excellent skills in R, Python, and/or SQL Background in economic/management consulting or finance Knowledge of financial concepts and principles Knowledge of crypto, decentralized finance, or smart contracts Demonstrated aptitude for research Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Associate Managing Consultant, Technical Program Management Technical Program Management/ Business Analyst Advisors & Consulting Services Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. Our Advisors & Consulting Services team combines traditional management consulting with Mastercard's rich data assets, proprietary platforms, and technologies to provide clients with powerful strategic insights and recommendations. Our teams work with a diverse global customer base across industries, from banking and payments to retail and restaurants. ________________________________________ Roles and Responsibilities You will lead technology programs and strategic initiatives with moderate oversight, managing project scope, requirements, technical delivery, stakeholder engagement, and implementation activities. You will collaborate across business and technology teams to ensure successful execution of client engagements while proactively managing risks, dependencies, and delivery outcomes. Client Impact • Lead multiple concurrent technology programs, product implementations

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Principal - Services Business Development Overview Mastercard Services is responsible for acquiring, engaging and retaining customers by managing fraud and risk, cybersecurity and improving the digital payments experience while providing value added services and using expertise, data-driven insights and execution. Role • Lead sales calls and new client development across all lines of Services Business for an assigned set of accounts in Mexico • Deliver against sales targets for existing accounts and/or contribute to Mastercard Worldwide deal bids • Capture senior and mid-level clients’ implicit business needs in addition to articulated requests, and identify most critical aspects of the problem • Translate objectives into key hypotheses and structure work for large/complex projects or ill-defined problems • Contribute to formal and informal pitches, from “storyboarding” through face-to-face presentation • Create succinct, persuasive written materials tailored to the “level” of the audience • Contribute to project delivery, quickly identifying shortcomings in projects and take remedial action All About You Education Needed: • Undergraduate degree required • MBA or relevant post graduate degree recommended Experience and Skills Needed: • Experience in top management

Become a part of our caring community The Counsel provides a full range of legal advice and services. The Counsel work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors. The Counsel typically a Legal generalist or provides counsel in a combination of disciplines. Begins to influence department’s strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Responsibilities: Be a part of the legal team -- use your legal expertise to drive healthcare strategy. Humana is seeking legal counsel who will support Humana and its management by: Providing legal advice and support for Humana’s Medicare Advantage lines of business; Advising on Medicare Advantage rules and regulations and related health care fraud and abuse laws, including the Anti-kickback statute and False Claims Act; Drafting contract provisions to address regulatory concerns; and Collaborating and consulting with leaders throughout the company in order to ensure full compliance with applicable laws and regulations, and protection against external risk. Required Qualifications: Juris Doctorate, with licensing in at least one state At least 3 years of experience in health law at a law firm or in-house health care organization Experience in Medicare, Medicaid, or similar regulatory work Strong legal research, analytical, and writing/oral communication skills Experience negotiating contracts </l