Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
Bank of America

Senior Data Scientist – Enterprise Credit

Bank of America

. Coordinate and review data collection, trend identification, and pattern recognition using advanced techniques .

Posted 11/2/2026full-timeUnited StatesSenior💰 $125,000 - $187,500 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Data Science and Artificial Intelligence, with strong programming skills in Python and SQL. Capable of leading projects, mentoring junior team members, and applying advanced techniques in Natural Language Processing and model risk management within the banking sector.

Highest-signal resume keywords
Data Science ExpertisePython ProgrammingNatural Language Processing (NLP)Project Management SkillsModel Risk Management

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
PythonSQLData AnalysisModel DeploymentNatural Language Processing (NLP)Machine Learning (ML)Data VisualizationQuantitative ModelingStatistical AnalysisRisk Mitigation
Soft Skills
Communication SkillsLeadershipMentoringCollaborationProblem-Solving
Tools & Technologies
PandasNumPyScikit-learnSpaCyNLTKPyTorchTensorFlowLarge Language Models (LLMs)Agile PracticesData Science Products
Industry Keywords
Enterprise CreditBankingData GovernanceModel ExplainabilityRegulated Financial Environments

Tech Stack

Tools & technologies
NumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact
  • Coordinate and review data collection, trend identification, and pattern recognition using advanced techniques
  • Drive decision-making and identify data-driven insights
  • Communicate how enterprise information products answer material banking questions and lead to decisions and actions
  • Apply agile practices to project management, solution development, deployment, and maintenance
  • Oversee technical documentation, business requirements, analytical solution specifications, and production implementation
  • Review quantitative models, data science products, data analysis reports, and data visualizations for quality and timeliness
  • Identify potential issues and develop controls to mitigate risk
  • Apply data science and artificial intelligence expertise to support business analytics
  • Evaluate proof of concepts for Enterprise Credit business cases using emerging AI technologies
  • Support Bank policy for artificial intelligence models and identify and mitigate associated risks
  • Mentor junior data scientists and analysts
  • Collaborate with lines of business and stakeholders to diagnose problems and develop solutions

Requirements

What you’ll need
  • 5+ years of work experience in a Data Science role or related field
  • Strong programming skills in Python and SQL
  • Experience building and deploying models
  • Project management skills, including prioritization, meeting deadlines, and completing high-profile projects or initiatives
  • Ability to lead and influence stakeholders across multiple levels and organizations
  • Ability to identify and remediate risks
  • 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 pandas, NumPy, scikit-learn, spaCy, NLTK, PyTorch, TensorFlow, or other advanced scientific/ML/NLP Python packages
  • Hands-on experience with Large Language Models (LLMs), including prompt engineering, fine-tuning, or parameter-efficient adaptation such as LoRA or adapters
  • Strong understanding of NLP architectures, transformers, embeddings, attention mechanisms, and vector similarity search
  • Experience operationalizing NLP/ML solutions, including model validation, monitoring, drift detection, and post-deployment improvement
  • 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
  • Experience mentoring junior data scientists
  • Minimum education requirement: High School Diploma / GED / Secondary School or equivalent

Benefits

Comp & perks
  • Affordable, competitive and flexible benefits
  • Support for physical, emotional, and financial wellness
  • Opportunities to learn, grow, and make an impact
  • Annual discretionary incentive award based on individual, line of business/group, and company performance
  • Paid time off
  • Resources and support for employees
  • In-office flexibility based on role-specific responsibilities and business needs