Financial Model Risk Management Lead

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. About the Capital Team The Capital team manages the financial foundation that supports Affirm’s lending and innovation. We lead the funding, liquidity, and risk management strategy across capital markets, treasury, deal structuring, analytics, and bank partnerships. The team secures efficient funding while supporting sustainable business growth. We balance cost, flexibility, and risk to ensure Affirm’s financial resilience through all economic cycles. By optimizing capital structure and managing liquidity, we help build a scalable and resilient financial platform. We’re looking for a smart, driven individual to join our Quantitative Markets team. The team is responsible for structuring and pricing Affirm’s debt funding deals, developing platforms and tools for optimizing funding strategies, and building models to analyze and predict the performance of Affirm’s consumer loans. The ideal candidate will have experience in structuring asset-backed transactions, working with rating agencies, and building quantitative models. Given the cross-functional nature of the role, the ideal candidate should have strong interpersonal and communication skills. What You’ll Do Work closely with the Capital Markets team to evaluate, structure and price consumer asset-backed transactions Develop and enhance capital structuring and pricing models tailored to Affirm’s consumer loan portfolio to enable efficient deal execution Build quantitative models to analyze and predict the performance of Affirm’s consumer loans Provide insights on capital markets deals to cross-functional teams for more optimal and efficient funding strategy and merchant pricing Partner cross-functionally with our Capital Markets, Treasury, Merchant Pricing, Credit, Commercial, Product and Engineering teams to evaluate funding, product

Who we are About the team Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers. What you'll do We're looking for machine learning engineers who want to build intelligent systems that provide financial data at scale. You'll play a key role in designing, training, and deploying ML models that improve the quality, accuracy, and usefulness of financial data across Stripe's ecosystem. Responsibilities Design, build, train, evaluate, deploy, and own ML models in production that improve transaction categorization, risk scoring, and data enrichment across Financial Connections Design and build large-scale ML systems that operate on diverse financial data from thousands of institutions Experiment and iterate on ML models (using tools such as PyTorch, TensorFlow, XGBoost) to achieve key business goals around data quality and accuracy Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliability Collaborate with product, data science, and engineering partners across Stripe to identify opportunities where ML can im

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust. What you'll do We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business. Data scientists on this team apply supervised and unsupervised machine learning, statistical mod

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Role Snorkel is hiring a Head of Security to build and lead our security function end-to-end — infrastructure security, application security, and governance, risk & compliance (GRC). You'll own the security function end-to-end — strategy, team, and execution — and operate as the primary security voice with customers, auditors, and the exec team. You'll report to the CTO. This is a builder's role: you'll take security from its current state to a mature, right-sized function as Snorkel scales, hiring and developing the team as needs grow. Key Responsibilities Security Leadership & Team Building Define Snorkel's overall security strategy,

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Trust and confidence is fundamental to the Lyft marketplace, and the Pay, Integrity & Identity (PII) Analytics team is charged with providing and ensuring that trust and safety to all customers. The PII Analytics team is one of the most critical teams that helps protect Lyft and enables the company to grow in a sustainable way. The team is fast-paced, high-energy, and meticulous in diagnosing emerging fraud patterns and preventing fraud loss before it can happen. We drill holes in all the products we launch and obsess over how to make our business impervious to fraud vectors. The team conducts a rigorous analysis of complex data sets and sets up multiple layers of business rules, models, and other processes to prevent potential fraud. We are a highly cross-functional team and regularly engage in discussion and reviews with stakeholders to prioritize plans for reducing fraud impact and introducing safety features. We’re looking for a rock-star to join a fast-paced environment to contribute to Fraud-related analysis and operations. This individual is responsible for investigating and developing solutions to prevent and mitigate third party fraud. This person will proactively identify fraud patterns and sources to minimize the company’s exposure to financial and reputational risk. The Senior Analyst will take ownership over multiple discrete fraud segments to develop and execute a strategy which addresses fraud in the earliest stages of detection. The Senior Analyst will define fraud prevention measures that are mindful of the impact on good user experience while inhibiting fraud actors’ ability to reach our platform. This person is quantitatively driven, detail-focused, and operations-savvy while ensuring the best possible customer experience. This individual possesses a high level of subject matte