Data Scientist I

NBMBAA

Charlotte (NC)

On-site

USD 90,000 - 130,000

Full time

4 days ago

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Job summary

Bank of America is seeking a Data Scientist I to analyze large-scale transaction data, develop value-added attributes, and support enterprise AI initiatives within the DSTRO program. The role focuses on data-driven decision-making, risk monitoring, and collaboration with cross-functional teams.

As part of the THOR Data Engineering team, you will contribute to model development, validation, and production readiness, leveraging SQL and analytics tools to deliver scalable, compliant solutions

Qualifications

Data analysis across large datasets to support decision-making and risk assessment.
Experience with data-driven insights and analytics documentation.
Familiarity with agile practices and cross-functional teamwork.

Responsibilities

Support development and maintenance of THOR data, AI, and model solutions.
Analyze large-scale transaction data using SQL and analytical tools to identify patterns, anomalies, risks, and opportunities.
Develop, evaluate, audit, and validate transaction categorizations and product enhancements.

Skills

Data Analysis

Data Cleansing

Data Quality and Validation

Agile Practices

Technical Documentation

Written Communications

Research and Analytical Methods

Data management

Data Visualization

Presentation Skills

Risk Awareness

Adaptability

Problem Solving

Attention to Detail

BofA Product Knowledge

Collaboration

US Market Awareness

Job description

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!

This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies

Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

Responsibilities

Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) 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 the business requirements and specifications related to the developed analytical solution and its implementation in production
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 both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables
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

Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM), responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across the bank. GRA is also responsible for model implementation, execution, forecasting and performance monitoring. The team drives innovation, process improvement and automation across these activities.

Overview of Data Science for Technology, Risk and Operations

Data Science for Technology, Risk, and Operations (DSTRO) enables the Bank's responsible adoption of Artificial Intelligence (AI) through governance, model oversight, model development, and enterprise data engineering. By providing AI and model risk governance, AI-driven solutions, and critical transaction data assets, DSTRO delivers the controls, infrastructure, and insights needed to strengthen risk management, enhance operational effectiveness, and drive enterprise value.

As a Data Scientist I supporting the THOR Data Engineering team and Enterprise AI Catalyst program, you will contribute to the development, enhancement, and maintenance of data, AI, and model solutions that address business needs across the enterprise. Working with senior model owners, developers, users, and cross-functional partners, you will analyze large-scale financial transaction data, investigate data patterns and anomalies, develop and validate value-added attributes, and support solutions throughout the product lifecycle, from ideation and testing through production and retirement.

Using SQL and other analytical and data science tools, you will help deliver scalable, compliant solutions that improve decision-making, streamline processes, and support business applications including revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. You will also identify opportunities to leverage and reuse existing AI technologies, models, data assets, and methodologies to reduce duplication and promote best practices.

The role will support THOR product enhancements, quality assurance, production validation, user analytics, technical documentation, training, and informational presentations. Success requires strong analytical and data science capabilities, attention to detail, intellectual curiosity, and effective relationship and project management skills.

Key Responsibilities

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.

Required Skills

Data Analysis
Data Cleansing
Data Quality and Validation
Agile Practices
Technical Documentation
Written Communications
Research and Analytical Methods
Data management
Data Visualization
Presentation Skills
Risk Awareness
Adaptability
Problem Solving and ability to find creative solutions to data problems
Strong attention to detail and curiosity about data patterns and anomalies
Understanding of BofA 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.