Data Support Manager

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth.

We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences.

These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in‑office culture that supports collaboration, engagement, and career development. Our approach includes clear in‑office expectations, while providing an appropriate level of flexibility based on role‑specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact.

Join us!

Under the GRM Data Strategy & Management leadership team, the Data Analyst / AI Engineer will design, build and operationalize quantitative models and agentic AI solutions for complex risk and data‑management use cases. This is a hands‑on role for an experienced practitioner who can move from problem framing and data discovery through experimentation, production deployment, monitoring and continuous improvement. The role will partner with risk subject‑matter experts, data owners, technology teams and governance partners to deliver explainable, scalable and controlled solutions in a highly regulated environment.

The successful candidate will combine strong Python and data engineering skills with basic understanding of data strategy, data lineage, metadata, data quality and data governance. The candidate should be able to translate business and control objectives into production‑grade data and AI products, while documenting data provenance, model behaviour, decisions and human oversight.

• Build agentic AI solutions that use large language models, retrieval‑augmented generation, tools, APIs and workflow orchestration to support research, analysis, decision support and operational processes.
• Develop robust Python services, reusable libraries, data pipelines and APIs that integrate structured and unstructured data from multiple Systems of Record.
• Create evaluation frameworks for ML and generative AI solutions, including accuracy, precision/recall, robustness, latency, cost, hallucination, groundedness and task‑completion measures.
• Implement appropriate human‑in‑the‑loop controls, guardrails, audit trails, access controls, fallback paths and approval checkpoints for agentic workflows.
• Partner with business and risk stakeholders to frame problems, define measurable success criteria and translate prototypes into scalable, production‑grade capabilities.
• Apply data strategy principles to identify authoritative sources, promote reuse, minimise redundant sourcing and align solutions to target‑state data architecture.
• Document and maintain end‑to‑end data lineage from source systems through transformations, features, models, prompts, agent actions and downstream outputs.
• Embed data governance requirements into…