Data Scientist II

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!

Position Summary:
This job is responsible for reviewing and interpretating large datasets to uncover revenue generation opportunities and ensuring the development of effective risk management strategies. Key responsibilities include working with lines of business to comprehend problems, utilizing sophisticated analytics and deploying advanced techniques to devise solutions, and presenting recommendations based on findings. Job expectations include demonstrating leadership, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

We are seeking a Data Scientist with experience in banking and finance to join our team. Data Engineer is a critical role for the BASE team, ensuring stable job monitoring and rapid production issue resolution during US business hours. The ideal candidate will have a strong background in statistical analysis, machine learning, and large language models (LLMs), with a strong ability to translate business problems into actionable data-driven solutions. A Data Engineer is essential to implement efficient data flows, enforce data management standards, enhance data quality, and support continuous delivery and release cycles. Without this role, the project risks delays in data readiness, gaps in data compliance, reduced quality of analytical outputs, and inability to support downstream systems effectively.

Responsibilities:

• Enables business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques to drive decision making and collection data driven insights
• Applies agile practices for project management, solution development, deployment, and maintenance
• Develops and reviews technical documentation, capturing the business requirements, and specifications related to the developed analytical solution and implementation in production
• Manages multiple priorities and ensures 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
• Delivers presentations in an engaging and effective manner through in-person and virtual conversations that communicates technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables
• Supports the identification of potential issues and development of controls
• Maintains knowledge of the latest advances in the fields of data science and artificial intelligence to support business analytics
• Analyze large financial datasets to extract insights and support business decisions.
• Develop, implement, and evaluate machine learning models and algorithms tailored to banking and finance use cases (e.g., risk modeling, fraud detection, customer segmentation).
• Apply and fine-tune large language models (LLMs) for tasks such as document analysis, customer communication, and regulatory compliance.
• Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
• Communicate findings and recommendations through reports, dashboards, and presentations.
• Work with data engineers to ensure data quality and pipeline reliability.
• Work with AI/ML engineers to build AI solutions.

Required Qualifications:

• Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related field.
• Proven experience as a Data Scientist in Banking or a similar domain
• Proficiency in Python or R, and experience with data science libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Hands-on experience with large language models (e.g., OpenAI GPT, Llama, or similar), including fine-tuning and prompt engineering.
• Strong knowledge of statistics, machine learning, and data mining techniques.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Experience with Big Data Platforms (Hadoop), Relational Databases (Oracle) and NoSQL Databases (MongoDB).
• Experience with Agentic AI and Agent Development.
• Familiarity with SQL and working with relational databases.
• Excellent problem-solving, communication, and collaboration skills.
• Experience with cloud platforms (AWS, Azure, or GCP) is a plus.

Desired Qualifications:

• Experience with NLP, deep learning, or time series analysis.
• Experience deploying models to production environments.
• Knowledge of regulatory requirements and compliance in banking and finance.
• Familiarity with MLOps practices and tools.
• Experience with Agile methodology and tools (JIRA or Rally)

Skills:

• Agile Practices
• Application Development
• DevOps Practices
• Technical Documentation
• Written Communications
• Artificial Intelligence/Machine Learning
• Business Analytics
• Data Visualization
• Presentation Skills
• Risk Management
• Adaptability
• Collaboration
• Consulting
• Networking
• Policies, Procedures, and Guidelines Management

Shift:

Hours Per Week: