SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
SentiLink is hiring a Manager, Risk Strategy to lead the model governance and risk function end-to-end. You'll manage a team of 3+ data scientists and governance professionals, setting long-term strategy and owning what great model governance looks like at the company—both strategically and in day-to-day execution.
The role sits at a critical intersection: SentiLink's real-time fraud detection models must satisfy customers' model risk teams, regulators, and auditors without slowing product velocity. You'll own this tension and drive the strategy to resolve it.
Key responsibilities include leading and scaling the governance team; owning core functions like performance monitoring, drift detection, fair lending assessments, governance documentation, validation, model inventory, and change management; setting strategy on what to automate, standardize, and where to exceed industry norms; managing cross-functional relationships with Data Science, Engineering, Partner Success, and Sales; owning direct customer relationships with model risk teams at banks and fintechs; preparing validation reports and governance documentation for leadership, customers, auditors, and regulators; and tracking governance findings through remediation.
This is a hands-on leadership role. You'll step in directly when needed to move work forward, mentor the team, or unblock customer deployments. Governance is a direct lever on company growth—the right person can define this function and scale it significantly.
Required: 8+ years in model risk management, model validation, governance, or quantitative risk, including proven experience building or scaling a governance/risk team (not just operating within one). 4+ years of people management experience building and scaling model risk or governance teams. Deep knowledge of model governance for financial institutions (SR 11-7, SR 26-2, OCC guidance, fair lending, regulatory landscape). Firsthand experience validating or governing ML/statistical models in a regulated environment. Genuine technical depth—able to read models, interrogate methodology, and work with data scientists. Working knowledge of Python and SQL proficiency. Strong bias for action, balancing governance rigor against speed with judgment. Strong analytical skills and excellent written/verbal communication. Bachelor's degree in a quantitative field (Math, Statistics, CS, Engineering, Economics, or related STEM). Must be legally authorized to work in and reside in the US.
Nice to have: Experience with fraud, identity verification, credit risk, or financial risk models. Experience supporting model governance with banks or regulators.
