Senior Data Scientist
About the role
This role is responsible for coordinating, reviewing, and optimizing data analysis to create revenue-generating opportunities and overseeing the development of effective risk management strategies. You will work with lines of business to identify and diagnose problems, utilize sophisticated analytics, and deploy advanced techniques to devise solutions while clearly communicating recommendations based on findings. The position requires demonstrating leadership, influence, accountability, and a commitment to fostering responsible growth for the enterprise.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development, with clear in-office expectations and flexibility based on role-specific responsibilities and business needs.
Responsibilities
- Coordinate and review data collection, trend identification, and pattern recognition using advanced techniques to drive decision-making and data-driven insights.
- Contribute to the adoption of enterprise information products by communicating how they answer material banking questions, leading to decisions and actions.
- Apply agile practices for project management, solution development, deployment, and maintenance.
- Provide oversight and support for technical documentation, capturing business requirements, specifications, and implementation in production.
- Review work products to ensure quality and timeliness of deliverables such as quantitative models, data science products, data analysis reports, or data visualizations.
- Mitigate risk by identifying potential issues and developing controls.
- Lead the design, development, and deployment of AI applications across multiple business domains, owning delivery accountability across planning, execution, testing, and production rollout.
- Design and implement AI-powered solutions, including LLMs, prompt engineering, and RAG pipelines.
- Evaluate and adopt emerging AI technologies (e.g., Copilot, Foundry, open-source frameworks).
- Develop and maintain backend systems using Python (FastAPI, data pipelines, AI/ML frameworks) and Java.
- Implement cloud-native patterns (Azure/AWS/GCP) and ensure system observability (logging, monitoring, alerting).
- 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 integrate AI solutions (LLMs, RAG, agents, ML pipelines) into enterprise platforms.
Requirements
- 10+ years of experience in software engineering and system design.
- Proven experience delivering large-scale enterprise applications and AI solutions.
Qualifications
Technical Skills
- Python (AI/ML, APIs, data engineering).
- Hands-on experience with AI/ML frameworks (OpenAI, Hugging Face, LangChain, etc.).
- RAG pipelines, embeddings, vector databases.
- RESTful APIs, distributed systems.
Architecture & Platform Skills
- Microservices, APIs, event-driven architectures.
- Cloud platforms (Azure preferred).
- Containerization (Docker, Kubernetes).
AI/ML Knowledge
- LLM-based applications and prompt engineering.
- Model lifecycle management (training, deployment, monitoring).
- AI governance, risk, and explainability (preferred in regulated industries).
Soft Skills
- Strong problem-solving and analytical thinking.
- Excellent communication and stakeholder management.
- Ability to operate in a fast-paced, ambiguous environment.
Desired Qualifications
- Experience in financial services or regulated industries.
- Exposure to Microsoft ecosystem (Copilot Studio, Foundry, Fabric).
- Familiarity with agent orchestration, MCP, and AI platform integration patterns.
- Experience with data privacy, compliance, and secure AI deployments.
Skills
- Artificial Intelligence/Machine Learning
- Business Acumen
- Presentation Skills
- Project Management
- Technical Documentation
- Data Visualization
- Risk Management
- Written Communications
- Adaptability
Schedule
1st shift (United States of America), 40 hours per week.