Data Scientist I
Bank of America
This job at a glance
- Who can apply
- New grads, no experience needed
- Must know
- Machine learningStatisticsData analysisBusiness analysisAgileProject management
- Work
- On-site in Charlotte
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning73%Statistics72%Data analysis44%Business analysis12%of 100 similar entry-level jobs posted in the US this week
- Listed
- Oct 27, 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies.
Key Responsibilities
- Performs business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis) to support decision-making and drive data-driven insights.
- Applies agile practices for project management, solution development, deployment, and maintenance.
- Creates and maintains technical documentation, capturing business requirements and specifications related to analytical solutions and their implementation.
- Manages multiple priorities and maintains 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 engaging presentations and engages in conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration.
- Mitigates risk by identifying potential issues and developing controls.
- Researches the latest advances in the fields of 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 established 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.
Requirements & Tech Stack
- SQL
- Agile Practices
- Machine Learning
- Artificial Intelligence
- Data Science
- Data Visualization
- Technical Documentation
- Data Analysis
- Data Cleansing
- Data Quality and Validation
- Written Communications
- Research and Analytical Methods
- Data Management
- Presentation Skills
- Risk Awareness
- Adaptability
- Problem Solving
- Attention to Detail
- DevOps Practices
- Application Development
- Collaboration
- Policies, Procedures, and Guidelines Management
- Networking
- Business Analytics
Qualifications
- Strong analytical and data science capabilities.
- Strong attention to detail and curiosity about data patterns and anomalies.
- Effective relationship and project management skills.
- Ability to collaborate effectively within and between cross-functional teams.
- Understanding of BofA Products, Policies, Procedures, and Guidelines.
- Awareness of the US marketplace and interest in major industries, consumer brands and financial transaction trends.
- Shift: 1st shift
- Hours Per Week: 40