Senior Data Scientist - Enterprise Credit

Bank of America • Chicago, IL

3d • $125,000 - $187,500 • Onsite

About The Position

At Bank of America, the Senior Data Scientist - Enterprise Credit coordinates, reviews, and optimizes data analysis to identify revenue-generating opportunities and oversee effective risk management strategies. The role partners with lines of business to diagnose problems, applies sophisticated analytics and advanced techniques to develop solutions, and communicates recommendations based on findings. It calls for leadership, influence, accountability, and a commitment to responsible growth.

The position evaluates proofs of concept for Enterprise Credit business cases using emerging AI technologies, assessing strategic alignment, feasibility, scalability, and value across the model portfolio. It supports Bank policy for AI models and helps identify and mitigate risks associated with advanced techniques. The Senior Data Scientist also mentors junior data scientists and analysts, supporting continuous learning and innovation.

Bank of America describes its work culture as inclusive and supportive of teammate development and wellness. The company is committed to an in-office culture that supports collaboration, engagement, and career development, with role-specific flexibility based on responsibilities and business needs.

Requirements

• At least 5 years of work experience in data science or a related field.
• Strong programming skills in Python and SQL and ability to learn.
• Interest in using data for business insight and experience building and deploying models.
• Willingness to learn and acquire needed knowledge and skills.
• Project management skills, including prioritization, meeting deadlines, and completing high-profile projects or initiatives.
• Collaborative attitude, strong work ethic, and personal initiative.
• Ability to organize, prioritize, and balance multiple efforts in a fast-paced environment.
• Ability to lead and influence stakeholders across multiple levels and organizations, aligning technical teams and business stakeholders to deliver actionable insights.
• Ability to identify and remediate risks in a timely manner.
• Ability to navigate the enterprise and source information across multiple functions.
• Strong verbal and written communication skills.
• General knowledge of Enterprise Credit businesses, processes, systems, and policies.
• Experience building and implementing Natural Language Processing (NLP) solutions from scratch.
• Experience with Python packages such as pandas, NumPy, scikit-learn, spaCy, NLTK, PyTorch, TensorFlow, or other advanced scientific, machine-learning, or NLP packages.
• Hands-on experience with large language models, including prompt engineering, fine-tuning, or parameter-efficient adaptation such as LoRA or adapters for enterprise use cases.
• Strong understanding of modern NLP architectures, including transformers, embeddings, attention mechanisms, and vector similarity search.
• Experience operationalizing NLP/ML solutions, including model validation, monitoring, drift detection, and post-deployment iterative improvement.
• Strong understanding of model risk, bias, explainability, and governance in regulated financial environments.
• Ability to document assumptions, limitations, and controls for NLP and generative AI solutions for senior stakeholders and risk partners.
• Experience mentoring junior data scientists and providing technical guidance on NLP, modeling best practices, and code quality.

Nice To Haves

• 6–10+ years of work experience in data science or a related field.
• Ability to integrate NLP solutions with structured and unstructured enterprise data sources, including APIs, databases, document stores, and search indices.
• Experience handling model inputs and outputs at scale, including chunking strategies, embedding pipelines, and production latency and performance tradeoffs.
• Experience designing multi-step or agentic workflows in which NLP models work across tools, data sources, or intermediate outputs, such as retrieval-augmented generation or planning-execution loops.
• Success applying NLP or LLM-based solutions to document-heavy domains such as credit, risk, compliance, policy interpretation, or underwriting.
• Experience supporting proof-of-concept to production transitions while balancing research innovation with enterprise scalability and controls.
• Graduate degree in Data Science, Engineering, Computer Science, a quantitative discipline, or a similar field.

Responsibilities

• Coordinate and review data collection, trend identification, and pattern recognition using advanced techniques to inform decisions and identify data-driven insights.
• Communicate how enterprise information products answer material banking questions and lead to decisions and actions, supporting their adoption.
• Apply agile practices to project management, solution development, deployment, and maintenance.
• Oversee and support technical documentation that captures business requirements and specifications for analytical solutions and their production implementation.
• Review quantitative models, data science products, analysis reports, and visualizations for quality and timely delivery, working independently and collaboratively.
• Identify potential issues, develop controls, and mitigate risk.
• Apply subject-matter expertise in advances in data science and artificial intelligence to support business analytics.
• Evaluate proofs of concept for Enterprise Credit business cases using emerging AI technologies, assessing strategic alignment, feasibility, scalability, and value across the model portfolio.
• Support Bank policy for AI models and identify and mitigate risks associated with advanced techniques.
• Mentor junior data scientists and analysts, fostering continuous learning and innovation.

Benefits

• Industry-leading benefits; this role is currently benefits eligible.
• Access to paid time off.
• Resources and support for employees.
• Eligible to participate in an annual discretionary incentive plan, with awards based on individual performance and behaviors, line-of-business or group performance and contributions, and overall company success.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: High school or GED