Job Description:Job Description: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.
Skills:- Adaptability
- Attention to Detail
- Business Analytics
- Technical Documentation
- Written Communications
- Agile Practices
- Application Development
- Collaboration
- Data Visualization
- DevOps Practices
- Artificial Intelligence/Machine Learning
- Networking
- Policies, Procedures, and Guidelines Management
- Presentation Skills
- Risk Management
Shift:1st shift (United States of America)
Hours Per Week: 40
