About the job
At Toast, we empower restaurants and local businesses to thrive in a digital landscape, enabling owners to operate efficiently, boost sales, foster customer engagement, and maintain employee satisfaction. Our mission is to build a comprehensive restaurant platform that enables businesses to adapt, take charge, and focus on their passion: cultivating the restaurants they love. With an unwavering commitment to our customers, the Toast team is equipped to assist restaurants in navigating challenging times through innovative technology, valuable resources, and a supportive community. Our purpose-built technology, crafted by industry experts, ensures that we meet today’s needs while investing in future experiences that will enhance the restaurant landscape.
Bready* to make a change?
As a Senior Analyst within our Model Risk Management team, you will play a pivotal role in overseeing the Model Risk Program, which encompasses conducting model validation reviews, managing the model risk inventory, and tracking model performance, particularly concerning Fraud and Generative AI Models. Collaboration with our Data Science Team, architects, engineers, and product managers will be key as you evaluate the risks associated with model design, implementation, and utilization across various product lines.
A day in the life (Responsibilities)
- Lead the execution of the Second Line of Defense (2LOD) Model Risk Management (MRM) program for high-risk models, focusing on Fraud detection models (Transaction Fraud & Merchant Fraud) and Generative AI / LLM-based systems deployed across Toast.
- Support the enhancement of the Model Risk Management framework, including policies, procedures, validation standards, governance documentation, templates, and best practices in alignment with evolving regulatory and industry standards.
- Implement model lifecycle standards across development, implementation, monitoring, recalibration, change management, governance, and decommissioning, ensuring robust controls for traditional ML models and GenAI systems (e.g., RAG architectures, copilots, AI-assisted decision tools).
- Contribute to the creation, risk-tiering, and ongoing maintenance of a comprehensive model inventory, encompassing assessments of model impact, intrinsic risk (complexity and methodology), reliance on model outputs, and emerging AI-specific risks.
- Conduct independent model validation reviews under senior leadership guidance, focusing on conceptual soundness,...
