Play a key role at the center of maintaining a strong and resilient organization. In Risk Management and Compliance, you help the business grow responsibly by identifying emerging risks and solving real-world challenges. This role offers the opportunity to work on impactful analytics that influence strategic decision-making. You will collaborate with stakeholders across the organization while developing innovative, data-driven solutions. Join a team that values curiosity, challenges the status quo, and strives to be best-in-class.
As a Wholesale Credit Risk Portfolio Analytics – Associate in the Wholesale Portfolio Analytics – Industry Analytics team, you will contribute to portfolio analytics and industry research initiatives supporting credit risk management. You will conduct both quantitative and qualitative analyses across industries and portfolios, helping us identify trends and emerging risks. You will also support the development of analytical frameworks that enable informed decision-making. Working closely with stakeholders, you will help translate complex data into meaningful insights that drive strategy.
Job responsibilities
Produce recurring and ad hoc portfolio analytics, including concentrations, rating migration, emerging risks, and performance trends
Transform large datasets into actionable insights for credit officers and senior stakeholders
Conduct thematic deep dives on priority risk topics
Design and execute stress testing and sensitivity analyses across scenarios
Develop and refine industry models to forecast financial outcomes based on macroeconomic indicators
Utilize Python and SQL to manage, manipulate, and analyze large datasets
Perform backtesting and validate models to ensure robust credit risk assessments
Lead portfolio and thematic research to identify emerging risk trends
Apply large language model techniques to synthesize structured insights from unstructured data
Collaborate with cross-functional teams to integrate analytics into risk management frameworks
Present analytical findings and insights clearly to senior stakeholders
Required qualifications, capabilities, and skills
Bachelor’s or Master’s degree in Mathematics, Statistics, Economics, Finance, or a related quantitative field
Experience in financial risk analytics, credit risk management, or data science
Proficiency in Python, R, or SQL
Strong analytical and problem-solving skills
Ability to work with large and complex datasets
Strong written and verbal communication skillsAbility to present complex analysis in a clear and structured manner
Strong collaboration and teamwork skills
High attention to detail and adaptability
Ability to build relationships with internal stakeholders
Interest in applying modern technologies within financial services
Preferred qualifications, capabilities, and skills
Experience in quantitative modeling using Python
Experience in publishing industry research or analytical reports
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As a Wholesale Credit Risk Portfolio Analytics – Associate in the Wholesale Portfolio Analytics – Industry Analytics team, you will contribute to portfolio analytics and industry research initiatives supporting credit risk management. You will conduct both quantitative and qualitative analyses across industries and portfolios, helping us identify trends and emerging risks. You will also support the development of analytical frameworks that enable informed decision-making. Working closely with stakeholders, you will help translate complex data into meaningful insights that drive strategy.
Job responsibilities
Produce recurring and ad hoc portfolio analytics, including concentrations, rating migration, emerging risks, and performance trends
Transform large datasets into actionable insights for credit officers and senior stakeholders
Conduct thematic deep dives on priority risk topics
Design and execute stress testing and sensitivity analyses across scenarios
Develop and refine industry models to forecast financial outcomes based on macroeconomic indicators
Utilize Python and SQL to manage, manipulate, and analyze large datasets
Perform backtesting and validate models to ensure robust credit risk assessments
Lead portfolio and thematic research to identify emerging risk trends
Apply large language model techniques to synthesize structured insights from unstructured data
Collaborate with cross-functional teams to integrate analytics into risk management frameworks
Present analytical findings and insights clearly to senior stakeholders
Required qualifications, capabilities, and skills
Bachelor’s or Master’s degree in Mathematics, Statistics, Economics, Finance, or a related quantitative field
Experience in financial risk analytics, credit risk management, or data science
Proficiency in Python, R, or SQL
Strong analytical and problem-solving skills
Ability to work with large and complex datasets
Strong written and verbal communication skillsAbility to present complex analysis in a clear and structured manner
Strong collaboration and teamwork skills
High attention to detail and adaptability
Ability to build relationships with internal stakeholders
Interest in applying modern technologies within financial services
Preferred qualifications, capabilities, and skills
Experience in quantitative modeling using Python
Experience in publishing industry research or analytical reports
#J-18808-Ljbffr
