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. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Overview of Global Risk Analytics
Bank of America Merrill Lynch has an opportunity for a Data Scientist within our Global Risk Analytics (GRA) function. GRA is a sub-line of business within Global Risk Management (GRM). GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America. GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard. GRA models follow an iterative and ongoing development life cycle, as the bank responds to the changing nature of portfolios, economic conditions and emerging risks. In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. GRA drives innovation, process improvement, and automation across all of these activities.          

Overview of Consumer Risk
Consumer Risk is primarily responsible for:
• Oversight and delivery of key regulatory reviews such as the Current Expected Credit Losses (CECL) accounting standard and the Comprehensive Capital Analysis & Review (CCAR), as well as other strategic initiatives, including data and infrastructure development and maintenance
• Planning and delivery of a coherent model risk management framework and infrastructure across Consumer. These efforts include the development of one universal platform for seamless model development and implementation, and improvements to the quality and consistency of the data sourced for all development and production purposes
• Developing and maintaining risk and capital models and model systems across Consumer product lines. Models and model systems provide insight into various risk areas, including loan default, exposure at default (EAD), loss given default (LGD), delinquency, prepayment, balances, pricing, risk appetite, revenues and cash flows
• Developing and implementing quantitative solutions on strategic Consumer Risk platforms. Outputs include GRA libraries that perform consumer risk model calculations, analytical tools, processes and documentation
• Conducts research and analysis to improve understanding and assessment of loan portfolios, models used, and forecast results
• Partners with Consumer lines of business, and front line Risk, Allowance, and Finance teams to ensure consistency and appropriateness of the team’s various processes

Overview of the Role
As a Data Scientist on the Consumer Risk team, your main responsibilities will include:
• Managing a portfolio of data intensive operational processes that span multiple complex technologies and infrastructures 
• Building and running operational processes, across large complex multi-sourced data, often on a wide range of quantitative models using applications and coding based solutions  
• Managing and monitoring controls across model execution and / or the sourcing and provisioning of complex data for multiple end-users 
• Managing cycle-over-cycle executions and shaping the strategic direction of operations in a highly regulated environment
• Interacting with multiple stakeholders to drive consistent on-time delivery of well-considered and thorough solutions, often with short delivery times
• Leveraging technical skills to improve, enhance, and automate existing processes 
• Providing regular updates to various stakeholders and senior leaders

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

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

Required Skills
• Masters’ degree in a quantitative discipline
• 2+ years of experience in model development, model validation, statistical work, data analytics or quantitative research, or PhD

Ability to manage and deliver:
• Cycle-over-cycle operational processes across data provisioning, model execution, and model performance monitoring
• Close collaboration with change agents driving operational excellence through strategic change
• Process execution while complying with various policies and regulations
• Code development and programming with tools such as Python, PySpark, SQL, Hadoop, Hive
• Additional experience with Unix/Linux, Shell Scripting, and SAS a plus

Strong operations management skills and techniques, including:
• Proficiency in the management of the full project life cycle – from inception to full technical and process implementation
• Proficiency in operating in a business and technical environment

Demonstrated personal qualities including:
• Strong understanding of process controls and safeguards
• Confident self-starter
• Quick learner and intellectually curious
• Strong communication skills, both oral and written
• Strong team player, able to lead and follow
• Strong influencing skills

Desired Skills
• Experience working for a financial institution; knowledge of retail banking products, services, processes, and systems
• Knowledge of model development / model implementation lifecycle
• Experience with data analytics / software development lifecycle tools (i.e. Alteryx, Tableau, Horizon / JIRA, etc.)
• Ability to deliver large scale projects involving changes to analytical processes, quantitative models, complex technology platforms, and analytical tools

Key Role Performance Measures
• Anticipation – Aware of downstream and upstream processes, pre-empts issues, acts on the front foot
• Analysis – Understands results, has instinct for errors/anomalies, can contextualize easily
• Adoption – Agent for change, creates plans, inventive, tests well, measures twice cuts once
• Adaptiveness – Reacts well to variation or curve balls, has versatility and applies solutions appropriately, not only identifies / anticipates road blocks but knows how to solve for them
• Articulation – Clear structured thorough communication, able to tailor messaging for a varied audience, can express things in different ways, uses communication to influence and get buy-in
• Application – Delivers results, understands the objectives and executes flawlessly, requires little hand holding, is consistent in delivery
• Adjudication – Management skills, judges and measures performance well, spots / recruits talent, can train / nurture / develop talent
• Alliance – Works as a team internally and externally, forges trusted relationships, is respectful / empathetic / flexible to others, delivers together with collaboration
• Accountability – Can set success criteria, develop metrics/measurement techniques well, identify the need and build and operate to SLAs, always aware of "how we are doing"
• Authority – Commands respect through thought / articulation / delivery, is seen as a leader, can influence others and take them on a journey, resolves conflict without tension or contention

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Job Tags

Full time, Remote job, Flexible hours, Shift work, Day shift,

Similar Jobs