Risk Analysis Specialist III

Bank of America•Jersey City, NJ

8d•Onsite

About The Position

This job is responsible for performing analytical requests, reporting and analysis, and assisting with modeling activities to help manage risk and minimize credit and operating losses. Key responsibilities include overseeing portfolio trends, developing data sets or queries to extract data, and supporting the production of internal and external reporting needs. Job expectations include effectively driving information and insights which have significantly impact regulatory, financial accountability, and directly impact to business policies and goals. The Data Connections Subject Matter Expert (SME) Lead is responsible for developing deep expertise in business processes, data sources, data flows, and system architecture to enable automated testing that delivers timely, actionable, and risk-focused insights into the operational health of Bank of America processes. The role serves as a key liaison between business, technology, and testing teams to establish scalable data connectivity solutions that support automation, analytics, and continuous monitoring initiatives.

Requirements

Demonstrates strong critical thinking and problem-solving skills, with the ability to understand end-to-end business processes, data flows, and technology dependencies.
Takes ownership of deliverables, effectively prioritizes competing demands, and drives high-quality outcomes in a fast-paced environment.
Identifies opportunities to improve processes, strengthen controls, and increase operational efficiency through automation, standardization, and continuous improvement.
Strong written, verbal, and presentation skills with the ability to communicate complex technical concepts to technical, business, and executive audiences.
Builds strong relationships across business and technology teams, effectively influencing stakeholders and driving alignment on priorities and solutions.
Demonstrates sound judgment, asks insightful questions, and translates complex requirements into clear, actionable recommendations.
Strong understanding of structured and unstructured data, database concepts, data architectures, and data integration patterns.
Proficient in SQL and Python, with experience analyzing data, troubleshooting issues, and developing scalable data solutions.
Experience working with enterprise data platforms and technologies such as Hadoop, Trino, and other large-scale data environments, along with advanced proficiency in Microsoft Excel and PowerPoint.
Bachelor’s degrees or above in fields including but not limited to: Finance, Economics, Mathematics, Computer Science, Statistics, Process and Mechanical Engineering, Operations Research, Data Science, Accounting, Business Administration
5+ years of relevant work experience

Nice To Haves

Business Intelligence
Data Visualization
Issue Management
Project Management
Risk Management
Business Acumen
Continuous Improvement
Risk Analytics
Stakeholder Management
Technical Documentation
Adaptability
Attention to Detail
Data and Trend Analysis
Performance Management
Regulatory Relations

Responsibilities

Develops and executes reporting to allow risk and business partners to effectively identify and manage risk in an effective manner
Identifies trends and manages the data design, portfolio trends, loss trends, and portfolio dynamics to ensure alignment with business strategies
Participates in various product strategic initiatives affecting multiple risk functions and lines of business to ensure company goals are met
Facilitates the development of database production processes and performance reports for senior management, using data mining and other advanced analytical techniques to aggregate data
Responds to complex ad-hoc requests for information from both internal and external parties
Coordinates cross-functional efforts to remediate data quality issues
Manages the outputs of controls and investigates alerts from the control checks
Partner with business stakeholders, application managers, and technology teams to understand business processes, data requirements, system architectures, and testing needs, translating these into scalable data connectivity solutions that support automation initiatives.
Design, implement, and optimize data connections that enable automated testing, analytics, and monitoring capabilities while leveraging emerging technologies and automation solutions to improve efficiency, scalability, and adoption of new platforms.
Lead cross-functional data quality, automation, and connectivity initiatives while driving process simplification, operational excellence, and continuous improvement across the end-to-end data onboarding and management lifecycle.
Ensure data connectivity processes operate in accordance with established governance standards, service level agreements, quality controls, and performance metrics while promoting sustainable, reliable, and compliant solutions.