Data Scientist II - Fraud Senior Model Governance

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 is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
 

Job Summary:

This job is responsible for reviewing and interpretating large datasets to uncover revenue generation opportunities and ensuring the development of effective risk management strategies. Key responsibilities include working with lines of business to comprehend problems, utilizing sophisticated analytics and deploying advanced techniques to devise solutions, and presenting recommendations based on findings. Job expectations include demonstrating leadership, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

Client Protection is looking for an experienced model developer / data scientist to join our team and help us combat financial crime. The role is responsible for providing model governance support across the entire model life cycle.

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

• 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

• Supports the identification of potential issues and development of controls

• Maintains knowledge of the latest advances in the fields of data science and artificial intelligence to support business analytics

• Developing advanced technical documentation for an array of internally- and vendor-developed models ranging from regression to sophisticated techniques including XGB, neural networks, graph

• Working closely with developers to understand how the model works and provide effective challenge to not only push back on methodology but also ensure results are accurate

• Partnering with technology and model users to schedule deployments and planning for future model installations

• Working with independent model risk management, legal and compliance teams to ensure models are fully validated and approved for usage

• Producing analytics to ensure early model results look consistent with expectations

• Conducting regular model monitoring and sharing performance results and analytical insights with model stakeholders and users

• Supporting Bank policy for Artificial Intelligence models and ensuring any risks of using advanced techniques are identified and mitigated

• Tracking model changes after deployment and ensure appropriate documentation reflects any adjustments, patches or updates

• Driving model performance analytics above and beyond Model Risk Management policy requirements, including granular performance monitoring, early trend detection, root cause analysis, and gap analysis.

• Serve as a subject matter expert across model’s live cycle

• Mentor junior data scientists and analysts, fostering a culture of contin