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!

Job Description:
Responsible for enabling analysis, modeling, and optimization through producing information products. Actively involved in the research and development efforts but spends significant amount of time with senior level business partners to develop strategy and coordination of projects. Primary requirement is not related to traditional programming or systems analysis skills but to the ability to create sophisticated, value-added analytic systems that support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. These systems must overcome issues of complex data (e.g., VLDB, multi-structured, big data, etc.) as well as deployment of advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to deliver insights. Promotes the adoption of enterprise information products through clearly communicating how enterprise information products answers material banking questions leading to decisions and actions. This role often possesses an advanced degree in hard science or another heavy quantitative business or social discipline. Manages a data science team.

Managerial Responsibilities:
This position may also have responsibilities for managing associates. At Bank of America, all managers at this level demonstrate the following responsibilities, in addition to those specific to the role, listed above.

• Diversity & Inclusion Champion: Breaks down barriers to create a more inclusive environment that supports company D&I goals.
• Manager of Process & Data: Challenges end-to-end process efficiency and effectiveness, champion data driven decision-making and removes obstacles to optimize operations.
• Enterprise Advocate & Communicator: Contributes to enterprise strategy and influence messaging to connect team contributions to business purpose, results, and success.
• Risk Manager: Inspects and challenges risk controls, governance and culture to ensure the timely identification, escalation, debate and remediation of risk across the organization.
• People Manager & Coach: Coaches to sustain and elevates organizational performance while differentiating to ensure pay for performance.
• Financial Steward: Efficiently allocates and manages resources across the organization to drive short and long term profitability.
• Enterprise Talent Leader: Inspects and manages the health of the bench to ensure succession for the organization, while supporting enterprise talent needs.
• Driver of Business Outcomes: Mobilizes organizational resources to deliver the full range of the bank's capabilities to meet client needs and to gain competitive advantage.

Skills:

• Business Acumen
• Executive Presence
• Presentation Skills
• Prioritization
• Strategic Thinking
• Continuous Improvement
• Performance Management
• Risk Management
• Succession Planning
• Workforce Diversity Management
• Adaptability
• Artificial Intelligence/Machine Learning
• Compensation Analysis
• Stakeholder Management
• Written Communications

The Data Science for Technology, Risk and Operations (DSTRO) team is seeking a Data Scientist Executive. The Data Science Executive role will report directly to the Head of DSTRO. Primary requirement is the ability to leverages Artificial Intelligence (AI), Machine Learning and emerging technology to improve the efficiency and effectiveness of testing, automating testing and testing related processes. In addition, this role develops innovative Natural Language Processing (NLP) solutions for Global Risk Management and the greater Enterprise with a focus on adding business value through measurable expense reduction and revenue generation. The ideal candidate will be proficient in finding patterns in data information that directly lead to revenue generation, risk mitigation, operational excellence or regulatory compliance.

Responsibilities include:
• Deliver technology solutions through innovation projects
• Lead a team or project to a target state of data science tools and techniques
• Build trusting partnerships with the Lines of Business to deliver data science service
• Apply state-of-the-art data science techniques to solve real business problems
• Provide insights into customer, client, product behavior to create broader impacts and share credit with colleagues during this process
• Execute on all Global Risk Analytics Model Development standards and serve as a role model for other data scientists on best practices in model development and model governance

Overview of Global Risk Analytics and Enterprise Independent Testing:
Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.

Overview of Data Science for Technology, Risk and Operations:
The Data Science for Technology, Risk and Operations (DSTRO) team, a sub-line of business within GRA, is responsible for developing, enhancing and maintaining the Enterprise Information Products (EIPs) dataset. Additionally, DSTRO leverages artificial intelligence to enhance the efficiency and effectiveness of Enterprise Information Testing (EIT) and oversees the development of Natural Language Processing (NLP) solutions. The team is also dedicated to advancing Data Science and Artificial Intelligence (AI) capabilities and execution within GRA, working closely with Global Technology, Global Operations, Model Risk Management, and the AI Policy, Strategy, and Governance teams to establish a robust operational framework for both vendor and internal technology and operations models.

Bank of America:
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!

Skills:
• Experience in leading and managing diverse project teams of varying sizes
• Experience in building, testing, or documenting models consistent with model development procedures and model risk management expectations
• Expert verbal and written communicator and can build trusting relationships with all stakeholders
• Drive an innovative culture, interact and communicate with senior-level business partners, lead and direct multiple projects, delegate work, decompose complex issues, and drive timely decisions

Required Technical Skills:

• Degree in a quantitative field demonstrating training and experience in quantitative finance, statistical modelling and/or data science (e.g., Computer Science, Statistics, Mathematics, Data Science)
• 5+ years of related work experience, such as model validation, model governance, model audit, model development or data science
• Good, applied statistics skills, such as distributions, statistical testing, feature engineering
• Understanding and applied knowledge of statistical and machine learning modelling techniques
• Excellent understanding of model governance at a regulated financial institution
• Technical writing skills

Desired Skills:

• Prior experience working in Model Risk Management or Model Audit or related areas
• Willingness and ability to support the Global Risk Management Site Leader in their location, facilitate in-person data science training for GRM associates in their location and lead by example on Workplace Excellence
• Prior experience working with teammates and stakeholders across the globe

Shift:
1st shift (United States of America)

Hours Per Week:
40