Senior Model Risk Manager
MercuryFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, along with a minimum of 4 years of experience in machine learning, demonstrating strong software engineering skills. Experience with risk modeling for financial use cases is required, and proficiency in ML techniques such as LLMs, deep learning, and sequence/tree-based models is preferred, alongside knowledge of credit/fraud risk and portfolio management. Advanced skills in Python programming, SQL, and data manipulation are also necessary. Familiarity with ML frameworks like TensorFlow and PyTorch, and cloud platforms like AWS Sagemaker, Databricks, or GCP Vertex AI, is expected.
As a Senior Machine Learning Engineer, you will be responsible for designing, developing, A/B testing, and deploying risk models while collaborating with data scientists to drive data-driven decisions. You will enhance credit and fraud models by incorporating innovative features and leveraging industry research, monitor feature and model health, and communicate changes in model decisions. Furthermore, you will explore and integrate advanced technologies like deep learning and LLMs in the risk domain, and lead by example to foster operational excellence and transformative change, expanding responsibilities as new products emerge.
Provides early wage access without fees
Earnin allows individuals to access their earned wages before payday without any fees or interest. Users can cash out a portion of their earnings and benefit from features like the "Balance Shield," which helps maintain their bank account balance. Unlike traditional financial institutions, Earnin operates on a model where users choose how much to pay for the service, fostering a community-driven approach. The company's goal is to create a fairer financial system that prioritizes accessibility and mutual support.