Fraud Model Developer Manager Manager Consultant in United States

About the Team The Account & Platform Integrity Operations team protects OpenAI’s ecosystem by ensuring that users, developers, partners, and organizations can access and build on our platform safely and responsibly. The team works across account integrity, fraud prevention, abuse detection, and platform risk to prevent bad actors from exploiting OpenAI’s products and developer surfaces. This role will sit within the Account & Platform Integrity Operations team while partnering closely with teams across the Ecosystem organization to ensure the platform can scale rapidly without compromising trust, quality, or safety. About the Role - Platform Operations Program Manager As OpenAI's developer ecosystem expands, we're building the operational foundation to support the next generation of plugins, MCP apps, agent skills, and integrations. As a Platform Operations Program Manager, you'll partner across Product, Engineering, Policy, Legal, Security, and Developer Experience to design the systems and operating models that enable ecosystem growth while maintaining quality, trust, and an exceptional developer experience. This role requires strong operational judgment, a deep understanding of developer platforms and APIs, empathy for the developer experience, and the ability to translate evolving product, platform, and policy requirements into scalable operational systems. Location: San Francisco, CA (Hybrid - 3 days in office) What You'll Do Own the operational processes that help developers bring apps, plugins, and integrations to market, from submission and review through launch, appeals, and ongoing monitoring. Manage external review partners and policy operations workflows, helping teams apply standards consistently while identifying areas where guidance, process, or quality expectations need to improve. Partner with Product, Engineering, Policy, Legal, Security, Developer Experience, and Go-to-Market teams to turn platform goals and requirements into clear, effec

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

About the Team At OpenAI, our Trust, Safety & Risk Operations teams safeguard our products, users, and the company from abuse, fraud, scams, regulatory non-compliance, and other emerging risks. We operate at the intersection of operations, compliance, user trust, and safety working closely with Legal, Policy, Engineering, Product, Go-To-Market, and external partners to ensure our platforms are safe, compliant, and trusted by a diverse, global user base. The Global Safety Response Operations team within the org provides 24/7 coverage for user safety, risk, and regulatory escalations across OpenAI’s products, handling the highest-priority cases that require human judgment and rapid response. The team operates as the core escalations management and delivery arm of OpenAI’s safety operations, ensuring that our products remain safe and aligned with our policies while enabling timely, empathetic, and consistent user support. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Please note: This role may involve exposure to sensitive content, including material that is sexual, violent, or otherwise disturbing. About the Role We’re looking for experienced Trust, Safety, and Risk Operations analysts who have subject matter expertise in one or more of the following areas: policy enforcement and content moderation, fraud and scam prevention, developer risk, or privacy and regulatory escalations. You’ll be on the front lines of safety escalation management, helping to triage and resolve urgent and sensitive cases. You’ll work across subject matter areas, systems, and processes to ensure operational excellence, develop process improvements and automations, and surface insights and trends. This is a 24/7 global operation that requires flexibility to work rotating shifts, including nights, weekends, and holidays, as part of an on-call coverage model. We use a hybrid work model of 3 days in the office per week and offer r

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. The Economy ML team sits at the center of this mission. We build ML and AI systems that power personalization, search, pricing, recommendations, and virtual item intelligence across Roblox Economy surfaces, including Avatar Marketplace, Payments, Developer Monetization and Subscriptions. As Roblox continues to invest deeply in AI and ML, this organization also plays a key role in advancing next-generation AI capabilities across the company through close partnership with Discovery, Foundation AI, Engine, Creator and product engineering teams. Our work spans both product impact and foundational ML innovation at Roblox scale. We are looking for a Director of Engineering to lead and scale Economy ML. This leader will define the strategy, organization, and execution model for a fast-growing ML organization spanning recommendation systems, ML infrastructure, search, content intelligence, and Generative AI applications. Why Roblox for ML/AI AI/ML is a top company priority , with strong executive support and long-term investment. Massive real-world scale: Millions of users, creators, and economic interactions every day. Unique technical challenges: Recommendations, pricing, fraud, search, and conte

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Our Fraud Intelligence team's mission is to turn fraud signals into insight that our EPD teams transform into improvements across Protect, IDV, Signal, and Guaranteed Payments. We believe transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention, and we ground our products in what adversaries are actually doing right now. As the Fraud Intelligence Lead, you will build and run a small, high-leverage team of Fraud Intelligence Analysts (and eventually a Staff Researcher) responsible for live casework across Protect, IDV, and Payments/ACH. You'll operate as a player-coach, hiring and coaching your team while staying close enough to the work to personally pick up casework and SEV response when needed. Responsibilities Team Building & People Leadership Set the casework quality bar: define what rigorous investigation, triage, and reporting look like for the team Coach analysts on investigation technique, pattern synthesis, and translating findings into product/model input Operating Model & Cross-PA Partnership Own coverage allocation across the Protect/IDV and Payments/ACH pods, including flexing assignments as volume shi

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Our Fraud team's mission is to help companies detect and prevent fraud using Plaid's financial network data. We believe that transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention. Our products — including Protect and Signal — operate at network scale and depend on real-world investigation and research to stay ahead of adaptive adversaries. As a Senior Fraud Researcher, you will sit at the intersection of live fraud investigation, applied data science, and product innovation. You will lead complex investigations, translate findings into detection improvements, and collaborate tightly with Data Science, ML, and Product teams to shape the next generation of Plaid's fraud capabilities. This is not a purely operational role — your research directly drives features, model inputs, and product design. Responsibilities: Live Fraud Investigation & Reconstruction Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces Provide support to day-to-day fraud operations including SEVs and alert triage Reconstruct attacker sequences and hypothesize actor intent and tooling Distill p

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid Protect is a real-time fraud intelligence product built on a unique advantage: Plaid’s network-level visibility across bank accounts, devices, identities, sessions, institutions, applications, and financial behavior. Protect helps customers detect first-party fraud, synthetic identities, account takeovers, and coordinated attacks that are difficult to see from a single application, account, or transaction. Trust Index turns that fraud intelligence into real-time fraud scores and actionable attributes. This team builds the systems that make this intelligence possible: low-latency inference, new data and model integrations, customer-facing APIs and attributes, safe rollouts, and feedback loops. Ti3 expanded Plaid’s fraud graph nearly 10x and, in early testing, detected up to 41% more fraud at the same false-positive rate. Learn more about Ti2 and Ti3 . We are a small, high-agency team working closely with Product, Data Science, and Machine Learning. We value demos over docs, conviction over consensus/alignment, builder schedule over meeting-heavy calendars. We’re scrappy and a talent-dense team that has high agency and high ownership. As a Staff Software Engineer on the Protect Core team, you wi

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Our Fraud team's mission is to help companies detect and prevent fraud using financial network data. We believe that transaction patterns, device signals, and behavioral data are an underleveraged tool in fraud prevention. The Fraud Consulting Lead is responsible for building and maturing our retro-as-a-service and POC program and driving adoption of our fraud products. The role sits between our data team and the customer (i.e., the role will not build the models, but will need to understand the output well enough to clearly and compellingly present the business case and work with technical stakeholders and customers.) Responsibilities: Own the retro and POC process end-to-end and collaborate with customers and internal stakeholders at Plaid Partner closely with customers to help them understand the ROI of Protect and make recommendations for implementing our fraud products Drive post-retro follow-through to convert retro results into production usage Serve as a feedback loop between customers and product to drive our Protect roadmap Qualifications: 5-10 years of experience in a customer-facing analytical role in fintech, financial services, or a related domain (e.g., software/tech) Experience worki

About the Team OpenAI’s Financial Engineering and Identity data science team owns how revenue flows through our products and builds the systems that enable people and organizations to access OpenAI products safely, seamlessly, and at global scale. Identity sits at the critical intersection of growth, trust, and user experience. The team owns the experiences and infrastructure behind sign up, sign in, account recovery, authentication, and identity integrations across both consumer and enterprise products. As OpenAI expands across products and markets, Identity plays an increasingly important role in helping more users get started quickly while protecting them from abuse, fraud, and account compromise. About the Role We're looking for the first dedicated Data Scientist to partner with the Identity organization. In this role, you will define how we measure success across the entire identity journey—from first-time sign up and onboarding through authentication, account recovery, and enterprise identity experiences. You'll develop the experimentation frameworks, metrics, and analytical approaches that guide product decisions while helping the team navigate one of Identity's core challenges: optimizing growth while maintaining trust and security. You'll work closely with Product, Engineering, Design, Abuse, Risk, and Go-to-Market teams to identify opportunities, quantify trade-offs, and influence strategy. Some questions can be answered through A/B tests. Others require observational analyses, causal inference, and judgment under uncertainty. This is an opportunity to shape the analytical foundations of a high-impact product area from the ground up. This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support. In this role, you will Define the north-star metrics and measurement frameworks used to evaluate the identity experience across consumer and enterprise products. Design and analyze experiments to optimize top-of

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: You have built and run production services in a high growth, rapidly scaling environment. You can debug live issues and restore systems quickly. You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Py

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 Data Scientist What is the opportunity? We are seeking a highly skilled and motivated Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains. What will you do? • Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards. • Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services. • Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions. • Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network. • Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions. • T