Data Scientist I

Bank of America•Charlotte, NC

1d•Onsite

About The Position

Bank of America is hiring a Data Scientist I to support the THOR Data Engineering team and Enterprise AI Catalyst program within Data Science for Technology, Risk, and Operations (DSTRO). DSTRO supports the Bank’s responsible adoption of AI through governance, model oversight, model development, and enterprise data engineering. The role contributes to developing, enhancing, and maintaining data, AI, and model solutions that address enterprise business needs. Working with senior model owners, developers, users, and cross-functional partners, the Data Scientist I analyzes large-scale financial transaction data, investigates patterns and anomalies, develops and validates value-added attributes, and supports solutions throughout the product lifecycle, from ideation and testing through production and retirement. The role uses SQL and other analytical and data science tools to deliver scalable, compliant solutions supporting revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. It also identifies opportunities to reuse existing AI technologies, models, data assets, and methodologies. Work includes THOR product enhancements, quality assurance, production validation, user analytics, technical documentation, training, and informational presentations. Global Risk Analytics (GRA), the broader business area, develops models and analytical tools for risk and capital measurement, management, and reporting across the bank, and is responsible for model implementation, execution, forecasting, and performance monitoring. GRA also drives innovation, process improvement, and automation. The position calls for strong analytical and data science capabilities, attention to detail, intellectual curiosity, and effective relationship and project management skills. Bank of America describes an in-office culture that supports collaboration, engagement, and career development, with flexibility based on role-specific responsibilities and business needs.

Requirements

Skills in data analysis, data cleansing, data quality, and validation.
Knowledge of agile practices and technical documentation.
Strong written communication, research, and analytical methods skills.
Data management and data visualization skills.
Presentation skills.
Risk awareness and problem-solving ability, including finding creative solutions to data problems.
Strong attention to detail and curiosity about data patterns and anomalies.
Understanding of Bank of America products, policies, procedures, and guidelines.
Ability to collaborate effectively within and between cross-functional teams.
Awareness of the US marketplace and interest in major industries, consumer brands, and financial transaction trends.
Adaptability and the ability to manage multiple priorities while maintaining quality and timeliness.

Responsibilities

Perform business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques such as machine learning, text mining, and statistical analysis.
Apply agile practices to project management, solution development, deployment, and maintenance.
Create and maintain technical documentation covering business requirements and specifications for analytical solutions and their production implementation.
Manage multiple priorities and deliver high-quality, timely quantitative models, data science products, data analysis reports, and data visualizations, independently and as part of a team.
Present technical concepts and analytical results to internal stakeholders in person and virtually, and develop professional relationships to support collaboration.
Identify potential issues and develop controls to mitigate risk.
Research advances in data science and artificial intelligence to support business analytics.
Support the development, enhancement, and maintenance of THOR data, AI, and model solutions throughout the product lifecycle.
Analyze large-scale transaction data using SQL and other analytical tools to identify patterns, anomalies, risks, and opportunities.
Develop, evaluate, audit, and validate transaction categorizations, value-added attributes, and product enhancements.
Apply quality-control, testing, documentation, and post-production validation practices.
Partner with model owners, developers, users, and business teams to understand requirements and deliver scalable, compliant solutions.
Identify opportunities to reuse existing AI technologies, models, data assets, and methodologies across the enterprise.
Support analytical requests, user documentation, training materials, and presentations for the THOR user community.