Fraud Model Developer Jobs

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role SoFi is seeking a Fraud Model Developer to join our Fraud Model Development team. In this role, you will develop, evaluate, and monitor machine learning models that support data-driven fraud and risk decisions across SoFi’s products and services, including Personal Loans, Student Loans, Credit Cards, and Crypto. You will build quantitative and machine learning solutions designed to reduce fraud losses, minimize false positives, lower operational costs, and protect SoFi members. You will also analyze model and product performance, identify key drivers of fraud losses, and translate complex findings into actionable recommendations for business and risk partners. This role requires strong experience in machine learning, statistical modeling, data analysis, and model performance monitoring. You will work closely with Fraud Risk, Fraud Operations, Product, Engineering, Finance, Accounting, and other business teams to develop scalable fraud-modeling solutions and ensure model performance and loss trends are clearly communicated. What you’ll do Develop quantitative, statistical, and machine learning models that reduce fraud losses, minimize false positives, and lower operational expenses associated with fraud complaints and disputes. Aggregate, clean, and synthesize large datasets from multiple data envir

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

About the Team Netlify runs on usage. Developers buy credits, teams consume compute and bandwidth, and enterprises commit to spend. The Accounts and Billing area owns how all of that works: the accounts foundation every customer signs into, the billing platform that meters and charges them, and the pricing and packaging model that sets what they pay. It sits at the center of how Netlify grows, and it touches Finance, Growth, UX, Sales, and the executive team. As a Staff Product Manager, you’ll help define and evolve Netlify’s monetization model, bringing a strong point of view while partnering across the company to make high-impact decisions, and you will build hands-on next to engineering, Finance, and design rather than run a team from above. You’ll collaborate closely with senior leaders, including the CEO and CFO, as we continue to evolve Netlify’s pricing and packaging strategy. What You'll Do Lead the strategy and evolution of pricing, packaging, and monetization, including plans and tiers, the credit and usage model, seat-versus-consumption economics, on-demand and overage rates, enterprise commitments and discounting, storage pricing, regional pricing, and annual plans. Ship billing as a product: metering accuracy, invoicing, payments, refunds, and customer-facing usage visibility, including the billing and usage interfaces enterprises are asking for. Steward the accounts foundation: sign-up and authentication, identity, orgs and teams and seats, roles and permissions, account security, and fraud and abuse at the top of the funnel. Build and lead the pricing and packaging experimentation program, using data, customer insight, and sound judgment to guide decisions: product analytics, conversion and activation, and credit-consumption telemetry. Partner with Finance to develop pricing approaches that balance customer value, business goals, and long-term sustainability. Partner with engineering and cross-functional stakeholders to set priorities, evaluate tradeo

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. 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 role is part of a 24/7 global operation team and will be expected to work a standard 5x8 work week, which includes covering the weekend shift each week (e.g., work weeks covering Saturday - Wednesday) We use a hybrid work model of 3 days in the Singapore 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. In This Role, You

About the Team At OpenAI, our User Operations team safeguards our products and users from legal risk, regulatory non-compliance, fraud, and abuse. The team operates at the intersection of operations, compliance, and user trust, embedded within the broader User Operations organization and collaborating cross-functionally with Legal, Governance Risk & Compliance, Policy and Engineering. We support a global and diverse user base across OpenAI’s suite of product offerings, and developer tools by managing sensitive inbound tickets, regulatory obligations, and escalations. Every user-facing action is grounded in our commitment to legal integrity, ethical practice, and regulatory excellence. About the Role We are seeking an independent, adaptive, and operations-minded Regulatory Operations Analyst to help scale and evolve OpenAI’s global regulatory and compliance operations from San Francisco. This role focuses on complex regulatory operations, including work under the EU Digital Services Act (DSA) and EU AI Act, as well as regulatory inquiries and complaints across the Americas, and Asia-Pacific. You’ll manage sensitive cases independently, exercise sound judgment on escalations, and work closely with Legal Counsel, Governance, Risk and Compliance (GRC), and other cross-functional partners. You’ll also bring a working understanding of privacy and intellectual property matters so you can recognize and escalate related issues when needed. Beyond frontline casework, you’ll help shape the documentation, workflows, tooling, and automation that support safe, scalable and regulatory and legal compliance operations. This role is essential to building scalable, high-integrity operations that protect user rights, meet our obligations under emerging and current regulations. You’ll also contribute to multi-phase transitions and automation efforts that support our long-term operational model. Please note: This role may involve exposure to sensitive or concerning content, including

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

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

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,

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 As a platform company powering businesses all over the world, Stripe processes payments, runs marketplaces, detects fraud, helps entrepreneurs start internet businesses from anywhere in the world, builds world-class developer-friendly APIs, and more. The engineering teams at Stripe work on the business logic for all of that. As a software engineering manager at Stripe, you'll lead teams that build and expand APIs, services, and experiences. You'll also work with partners to launch new markets and vertical capabilities. Stripe Terminal helps our users extend their online presence to the physical world. The mission of the Terminal team is to make it as easy for businesses to accept in-person payments as the Stripe API has done for online payments—building for Unified Commerce. With Terminal, businesses can unify their in-person and online experiences, unlocking payments use cases that are right for their business model—whether it's creating a modern retail experience, extending their website to a pop-up store, or enabling a mobile point-of-sale at their next event. Within Terminal, the Commerce team focuses on the following to help make Unified Commerce a reality for businesses across the globe. Enterprise features—on-reader forms, tipping, gift cards Payment features—DCC, surcharge, multi-capture Point-of-sale integrations—enterprise-focused integrations Low-code and no-code—solutions that will enable our users to onboard quickly What you'll

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 The Stripe Dashboard helps millions of people around the world run their business—from managing integrations and analyzing fraud to resolving customer issues. The next chapter is about transforming the Dashboard into a "power tool" for payment professionals. The Dashboard team is responsible for the scaffolding of the Dashboard (e.g., navigation, search, settings), governing frameworks (e.g., information architecture), and core experiences that set the standard (e.g., managing your customers, customizing your home page). We're hiring a product manager to shape the Dashboard strategy, amplify its impact across the company, and accelerate Stripe's mission to increase the GDP of the internet. What you'll do You'll evolve the Dashboard to meet the needs of any business model. Improve wayfinding mechanisms to increase user productivity and product discovery. Shape the information architecture to encourage interoperability. Develop a strategy and roadmap for a more personalized Dashboard. Write the playbook for interoperability across the numerous layers of indirection in the Dashboard. Partner with third-party developers to understand how the Dashboard can better serve their needs. Responsibilities Make the Dashboard easier to use and more powerful Own the strategy and roadmap that makes the Dashboard uniquely good for any business model Collaborate with engineering and design across time zones (PST, EST, CET) to ship high-impact functionality th