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Design, build, and operate production backend systems powering financial products. Own services end-to-end, implement event-driven distributed systems (Pub/Sub), instrument services with metrics, use SQL and analytics to evaluate performance, and ship improvements via CI/CD on GCP.

Provide frontline support via email and live chat, troubleshoot customer issues, report product bugs to Product and Engineering, gather user feedback, and recommend product and support improvements to improve adoption and satisfaction.

Build and validate predictive models (fraud, underwriting, payouts), perform data research and analysis, productionize models with engineers, iterate on model performance, present results, and help establish applied science and ML best practices across the company.

Develop, validate, and productionize ML models (fraud detection, risk underwriting, predictive analytics). Conduct data research, implement research papers, collaborate with engineers/product to deploy and iterate models, and communicate findings to stakeholders while building ML practice.

The Product Manager will develop user-facing products, analyze data, and manage product features to optimize user experiences in financial services.

As a Risk Analyst, you will evaluate product safety, analyze data using SQL, improve policies, and enhance user experience.

Lead Customer Experience & AI Operations by designing AI-powered workflows, improving metrics like CSAT, and managing a team of specialists to enhance customer satisfaction.