At Bank of America, the business problem is to uncover revenue generation opportunities and ensure the development of effective risk management strategies by reviewing and interpreting large datasets. This involves improving portfolio risk, profitability, performance forecasting, and operational performance for customer products, specifically aiming to reduce fraud losses, lower false positive impacts, and improve client experience.
Requirements
- Minimum of 4 years of experience in data and analytics
- Must have familiarity with Graph databases (e.g. TigerGraph, Neo4J) and graph query languages
- Must be proficient with SQL and one of SAS, Python, or Java
- Expertise handling data across its lifecycle in a variety of formats and storage technologies (e.g., structured, semi-structured, unstructured; graph; hadoop; kafka)
- Expertise in data analytics and technical development lifecycles including having coached junior staff
- Deep understanding of graph databases, graph algorithms, and experience developing graph schemas
- Understanding of advanced machine learning methodologies including neural networks, ensemble learning like XGB, and other techniques
Responsibilities
- Enables business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques to drive decision making and collection data driven insights
- Applies agile practices for project management, solution development, deployment, and maintenance
- Develops and reviews technical documentation, capturing the business requirements, and specifications related to the developed analytical solution and implementation in production
- Maintains knowledge of the latest advances in the fields of data science and artificial intelligence to support business analytics
- Manages a roadmap of data science use cases for technical development and implementation to the production environment in close partnership with Bank of America Technology
- Performs complex analysis of financial models, market data, financial data, and portfolio trends to understand product performance and improve portfolio risk, profitability, performance forecasting, and operational performance
- Link Analysis/Graph analytics to find and mitigate densely connected fraud networks
Other
- Job expectations include demonstrating leadership, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.
- Job expectations include working with counterparts within the Line of Business, across the technology organization, and risk teams.
- Manages multiple priorities and ensures 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 presentations in an engaging and effective manner through in-person and virtual conversations that communicates technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables
- Excellent communication and influencing skills
