Senior Data Scientist - Enterprise Credit

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!

Job Description:
This job is responsible for coordinating, reviewing, and optimizing data analysis to create revenue generating opportunities, and overseeing the development of effective risk management strategies. Key responsibilities include working with lines of business to identify and diagnose problems, utilizing sophisticated analytics, and deploying advanced techniques to devise solutions, and clearly communicating recommendations based on findings. Job expectations include demonstrating leadership, influence, accountability, and a commitment to fostering responsible growth for the enterprise.

This job is responsible for driving accurate, complete, and timely delivery of data. Key responsibilities include working with business stakeholders and technology teams to direct data management activities and ensure availability for use by appropriate consumers. Job expectations include managing execution within the Enterprise data management standards, data quality, and control practices.

The Data Initiative & Strategy (DIS) team, within Enterprise Credit Analytics & Transformation Strategy (ECATS), is responsible for delivering high-quality, fit-for-use data and information that supports Global Banking and Enterprise Credit objectives. DIS defines and enhances Enterprise Credit data processes, including platforms, reporting, governance, data management, and data remediation. 
  

This Senior Data Scientist role supports the DIS team with a primary focus on model data development, production support and operational continuity. The role is responsible for executing and maintaining established data processes, ensuring consistent, accurate, and timely delivery of data used in regulatory, risk, and business activities. The role supports adherence to Enterprise data quality standards, and identifies issues across data capture, transport, and use, contributing to stable and controlled data environments. In addition, the role contributes to the development of value-added analytics and solutions that support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. The role will interact with and provide direction to supporting Technology teams to ensure alignment with data and process requirements. A strong understanding of Enterprise Credit processes, organizations, data, and systems is required. Traditional systems analysis skills are a plus.
 

Responsibilities:

• Coordinates and reviews data collection, trend identification, and pattern recognition, using advanced techniques to drive decision making and identification of data driven insights
• Contributes to the adoption of enterprise information products through communicating in a clear manner how enterprise information products answer material banking questions leading to decisions and actions
• Applies agile practices for project management, solution development, deployment, and maintenance
• Provides oversight and support of technical documentation, capturing the business requirements, and specifications related to the developed analytical solution, and implementation in production
• Reviews work products to ensure adequate quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports,