Market Risk Analyst Jobs in North Carolina (NOW HIRING)

NOTE: This position is not eligible for current or future visa sponsorship.

The Market Risk Data Analytics Specialist will support Market Risk Management through data analysis, reporting automation, risk analytics, and technology-enabled process improvement. This role is intended for a hands-on analytical professional who can work with market risk data, build and maintain reporting tools, investigate data quality issues, and help modernize risk processes using VBA, SQL, Python or similar tools, and emerging AI-enabled capabilities.

The successful candidate will partner with Market Risk, Front Office, Technology, Finance, Model Risk, Operations, and other control functions to improve the accuracy, transparency, efficiency, and auditability of market risk reporting and analytics.

Key Responsibilities

• Develop, maintain, and enhance market risk reporting tools, dashboards, data extracts, reconciliation processes, and analytical templates used to monitor trading and capital markets risk.
• Use VBA, SQL, Excel, Python, and other analytical tools to automate recurring market risk processes, reduce manual effort, improve controls, and strengthen reporting consistency.
• Analyze market risk data, including VaR, stress testing, sensitivities, Greeks, P&L, exposures, limit utilization, back-testing results, and risk factor movements.
• Investigate and resolve data quality issues related to position data, market data, risk factor data, P&L, model outputs, and downstream reporting exceptions.
• Support data lineage, data validation, and control documentation for market risk reporting processes, including evidence needed for audit, regulatory, and governance reviews.
• Partner with Market Risk Managers and quantitative teams to identify drivers of changes in portfolio risk and explain material movements in risk metrics.
• Assist with model monitoring, back-testing, proxy analysis, stress scenario analysis, data reviews, and recurring committee or senior management reporting.
• Evaluate opportunities to apply AI, machine learning, natural language processing, or intelligent automation to improve market risk research, documentation, reporting, anomaly detection, workflow efficiency, and management insights.
• Contribute to the development of AI-enabled analytics in a controlled and transparent manner, including documentation of data sources, assumptions, controls, human review points, limitations, and governance considerations.
• Work with Technology and data teams to support database enhancements, data acquisition, data storage, process redesign, and modernization of market risk infrastructure.

Ideal Candidate Profile

The ideal candidate is a market risk data analytics professional who combines strong technical development skills with practical risk management knowledge. The individual should be comfortable working with imperfect data, investigating issues from source systems through final reporting, automating manual processes, and explaining analytical results clearly. The role requires someone who can improve today's reporting environment while also helping the team evaluate responsible, controlled uses of AI and modern analytics to support future market risk capabilities.

• Bachelor's degree in Finance, Economics, Mathematics, Statistics, Computer Science, Engineering, Data Science, Quantitative Finance, or related analytical discipline.
• Minimum of five years of experience in financial services, market risk, trading risk, quantitative analytics, data analytics, risk reporting, model monitoring, or a related capital markets function.
• Strong working knowledge of market risk concepts, including VaR, stress testing, sensitivities, P&L, risk factor movements, limit monitoring, back-testing, and data quality controls.
• Advanced C#, Excel and VBA skills, including the ability to build, maintain, troubleshoot, and enhance analytical tools and automated reporting processes.
• Strong SQL skills, including querying, joining, validating, reconciling, and analyzing large datasets from risk systems, databases, or reporting platforms.
• Experience with Python, R, Power BI, Tableau, Alteryx, or similar analytics, visualization, or automation tools.
• Ability to translate business and risk requirements into practical data solutions, reporting enhancements, and process improvements.
• Strong analytical, problem-solving, documentation, and communication skills, with the ability to explain technical findings to both technical and non-technical stakeholders.
• Experience working with control functions, audit requests, regulatory reviews, data governance standards, or model governance expectations.

Technical Skill Set

• Required: Advanced Excel, VBA, SQL, data validation, report automation, analytical troubleshooting, and market risk reporting.
• Strongly Preferred: Python, Power BI, Tableau, data visualization, database querying, risk dashboard development, and process automation.
• AI / Emerging Technology: Exposure to generative AI, machine learning, natural language processing, AI-assisted documentation, prompt engineering, AI governance concepts, or AI-enabled analytics.
• Market Risk Analytics: VaR, stress testing, sensitivities, Greeks, P&L attribution, back-testing, proxy analysis, limit monitoring, and risk factor analysis.

Preferred Skills/Experience

• Master's degree or master's program in Quantitative Finance, Financial Engineering, Mathematics, Statistics, Data Science, Computer Science, Economics, Finance, Analytics, or another relevant quantitative field is a plus.
• Hands-on experience with AI, machine learning, natural language processing, generative AI tools, intelligent automation, or AI-assisted analytics in a risk, finance, data, or technology environment.
• Experience with market risk systems or data environments such as RiskMetrics, Bloomberg, Calypso, Murex, Adenza, internal risk databases, data warehouses, or comparable platforms.
• Knowledge of regulatory risk concepts such as Basel market risk requirements, FRTB, Volcker-related controls, model monitoring, capital reporting, or regulatory exam support.
• Experience designing dashboards, exception reports, workflow tools, or analytics that improve risk transparency, operational efficiency, and management decision-making.
• Familiarity with data governance, data lineage, data quality frameworks, controlled EUC environments, software development lifecycle practices, or change management processes.
• Ability to work independently, manage multiple priorities, challenge data issues constructively, and build effective partnerships across Market Risk, Technology, Finance, Operations, Model Risk, and Front Office teams.

LOCATION EXPECTATIONS: This role requires working from a U.S. Bank Location three (3) or more days per week.

NOTE: This position is not eligible for current or future visa sponsorship.