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As a Senior Associate in Data Science, you will optimize and deploy machine learning models while collaborating with cross-functional teams to analyze data and derive insights for strategic decision-making in consumer credit risk management.

Lead the Managing Data Steward team for Small Business Bank to define and execute data management strategy, governance, quality controls, and data product development. Drive adoption of open-source and cloud-native (AWS) technologies, oversee data catalog health, monitor KRI's, manage data issue resolution, and report insights using advanced visualization. Coach and develop a high-performing analytics team while partnering with engineering and enterprise functions to standardize data flows and migrate on-prem systems to cloud.

Lead and mentor a team building distributed microservices and full-stack cloud solutions. Collaborate with product managers to deliver scalable AWS/GCP/Azure-based systems using languages like JavaScript, Java, TypeScript, Python, Go, and container orchestration (Docker, Kubernetes). Drive technical direction, participate in tech communities, and ensure solutions meet regulatory needs.

Lead cyber and technology risk assessments for retail banking, define mitigation strategies, prioritize and implement controls, integrate AI governance, analyze data to inform policy, engage stakeholders, and coach teams to scale risk management innovations.

Lead cross-functional partnerships between product, tech, and risk to maintain transaction processing controls. Design and document process workflows, ensure audit readiness, manage risk assessments and remediation, mentor junior staff, and drive continuous process improvements to reduce manual effort and maintain regulatory compliance.

This role involves leading the development of AI-powered products, optimizing large scale AI systems, and mentoring cross-functional teams. It focuses on designing and deploying AI components, contributing to the technical vision, and applying cutting-edge AI techniques.

Lead technical vision and architecture for Risk Technology, design scalable resilient systems, mentor engineers, contribute high-quality code, and drive cross-organizational technical strategy and reusable solutions.

Lead design, build, deploy, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize production LLM performance (cost, latency, throughput) and contribute to long-term technical vision.

Serve as the primary SME for transaction processing risk initiatives, partnering with product, tech, and risk to ensure processes are documented, efficient, and audit-ready. Drive remediation, manage assessments, testing, and regulatory requests, and maintain L2 process documentation, procedures, and team standard work to support continuous audit readiness and process excellence.

Lead technical design and delivery of scalable APIs, data contracts, and cloud-native platform services for large-scale customer data. Drive architecture for GraphDB and distributed systems, enable self-service onboarding and developer productivity, ensure resiliency/observability, automate operations, and mentor engineering teams while aligning cross-functional platform and product stakeholders.