at J.P. Morgan
Bulge Bracket Investment BanksPosted 4 days ago
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**London-based Wholesale Credit Risk Portfolio Analytics - Associate** expertly balances quantitative and qualitative analyses to identify trends and emerging risks. Collaborating across teams, they produce recurring analytics and decipher complex data into actionable insights for credit officers. Proficiency in Python, SQL, and strong communication skills are essential, with a background in Financial Risk Analytics or Data Science. Drive strategy with data-informed decisions, refining industry models and stress testing scenarios.
- Compensation
- Not specified
- City
- London
- Country
- United Kingdom
Currency: Not specified
Full Job Description
Location: LONDON, United Kingdom
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
- Bachelors or Masters 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 skills
- Ability 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
