Senior Data Scientist

Job Description

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!

This job is responsible for coordinating, reviewing, and optimizing data analysis to create revenue generating opportunities, and overseeing the development of effective risk management strategies. Key responsibilities include working with lines of business to identify and diagnose problems, utilizing sophisticated analytics, and deploying advanced techniques to devise solutions, and clearly communicating recommendations based on findings. Job expectations include demonstrating leadership, influence, accountability, and a commitment to fostering responsible growth for the enterprise.

• Lead design, development, and deployment of AI applications across multiple business domains
• Own delivery accountability across planning, execution, testing, and production rollout
• Design and implement AI-powered solutions
  , including: (LLMs, prompt engineering, RAG pipelines
• Evaluate and adopt emerging AI technologies (e.g., Copilot, Foundry, open-source frameworks)
• Python (FastAPI, data pipelines, AI/ML frameworks)
• Cloud-native patterns (Azure/AWS/GCP)
• Ensure system observability (logging, monitoring, alerting)

• Coordinates and reviews data collection, trend identification, and pattern recognition, using advanced techniques to drive decision making and identification of data driven insights
• Contributes to the adoption of enterprise information products through communicating in a clear manner how enterprise information products answer material banking questions leading to decisions and actions
• Applies agile practices for project management, solution development, deployment, and maintenance
• Provides oversight and support of technical documentation, capturing the business requirements, and specifications related to the developed analytical solution, and implementation in production
• Reviews work products to ensure adequate quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment
• Mitigates risk by identifying potential issues and developing controls
• Possesses deep knowledge and subject-matter expertise of the latest advances in the fields of data science and artificial intelligence to support business analytics
• Lead end-to-end delivery of AI and non-AI software solutions across multiple projects
• Design and implement scalable architectures (microservices, cloud-native, event-driven)
• Build and maintain backend systems using Java and Python
• Develop and integrate AI solutions (LLMs, RAG, agents, ML pipelines) into enterprise platforms

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