Teams at Possible Finance

Respond to customer inquiries through email, callbacks, chat, and phone; classify and investigate issues, resolve them using knowledge resources, and escalate complex cases to higher-tier teams. Maintain ownership of requests and provide timely updates through resolution. Support cross-training and backup coverage across Operations while developing knowledge of company products, services, and mission.

Own and build the company’s machine learning infrastructure, including a shared feature store, model-serving systems, drift monitoring, and unified deployment pipelines. Establish long-term MLOps standards and processes from the ground up, while collaborating with data scientists and engineers to drive adoption and improve production model reliability.

Own data science for payment performance, optimization, timing, retry strategies, monitoring, experimentation, and fraud detection. Build payment-health scorecards, anomaly monitoring, payment-risk models, and production ML systems using Python, SQL, PySpark, Databricks, and MLOps tooling. Partner with Engineering, Product, and Risk to shape payment strategy and roadmap while applying causal inference, feature engineering, and production model monitoring.