Lead, Credit Risk Analytics

The Opportunity

As the credit risk analytics lead within the Credit Risk Management team you will be involved with quantitative model implementation, development, and analysis and their business applications.

The ideal candidate will join a quantitative team and lead to enhance ERM’s analytical and reporting capabilities, by expanding the use of existing models and their business applications as well as designing and developing new tools and risk frameworks.

You will work with capital, credit, market and portfolio risk teams, and ERM more broadly. This is an excellent opportunity to collaborate with risk, investment and finance teams, and enterprise technology (including data science) teams.

The Team

Part of the Capital & Investment Risk Management team within ERM, the Credit Risk Management team’s mission is to manage portfolio credit, counterparty, and country risks across the enterprise in collaboration with key internal stakeholders in the Investment Management and CFO, as well as external counterparts.

Members of the team bring expertise and experience across a range of risk measurement and management disciplines, and also provide comprehensive and insightful quantitative analysis to support senior team management prepare recommendations that drive credit strategy.

The Impact

Make sure to read the full description below, and please apply immediately if you are confident you meet all the requirements.

• Lead the efforts to automate and expand the use of Moody’s credit risk tools in place today and assist in building frameworks with multiple business applications in capital, credit and portfolio risk management.
• Lead and mentor junior quantitative analysts.
• Lead the efforts in building credit risk measurements and credit VaR for various applications including portfolio benchmarking.
• Assist in leading the efforts to implement, develop and enhance ERM’s analytical capabilities related to quantification of credit, investment risks in the portfolio.
• Building on the existing data platform, lead efforts to process data requirements or enhance existing data frameworks, understand, and present data and analytics from insightful and actionable perspective with MassMutual’s wide range of asset classes.
• Assist in developing and syndicating new approaches for measuring portfolio credit & market risk, in the context of different accounting and capital regimes, including asset and liability impacts, with a particular emphasis on economic capital.
• Use of Python / SQL in the analytical work. Also, use of spreadsheets and VBA to do prototyping and analyze data.
• Lead complex initiatives including those are cross-functional with broader impact in Credit Risk and become a key participant and partner with those teams and stakeholders.
• Ongoing evaluation and / or review of risk measures of multiple asset classes and interaction with first line risk takers
• Liaise and collaborate with business stakeholders, quantitative model developers, technology.
• Assist the efforts to strengthen ERM’s use and development of tools and analytics to support derivatives counterparty risk & portfolio concentration risk.
• Assist in expanding use of quantitative models to support credit / investment and capital risk analysis, and stress scenario testing.
• Scope and implement modeling, including building out requirements where not yet fully defined or understood.

The Minimum Qualifications

• Minimum 7 years of relevant work experience in investment (credit / market) quantitative risk analytics
• Experience in leading projects in quantitative analytics capacity.
• Moderate to high level skills in Python and SQL and development skills
• Strong quantitative model development & implementation skills and ability to validate analytical results.
• Experience in quantitative risk modeling across a wide range of asset classes and relevant product knowledge in an investment setting.
• Ability to process and understand various data requirements in investment analytics.
• Bachelor’s and / or Advanced degree in a quantitative discipline
• Desire to use your quantitative and programming skills in a hands-on setting to deliver new functionality.

The Ideal Qualifications

• 7-10 years of relevant work experience is desirable.
• Master’s degree or PhD in Computer Science, Financial Engineering, Mathematics, Physics, engineering or similar quantitative discipline is preferred.
• Knowledge and experience working with public and private credit securities, structured and real assets, derivatives and hedging risk management.
• Experience in using Moody’s Analytics credit risk tools.
• Previous experience working on liability driven investing projects within an insurance company.
• Experience applying machine learning techniques and AI tools in the financial industry.
• Experience in implementation & migration quantitative models to cloud-based platform.

What to Expect as Part of MassMutual and the Team

• Regular meetings with senior leaders of the Credit Risk team and the Capital and Investment risk team
• Close work and collaboration with subject matter experts in ERM, Investment management & ETX project teams
• Focused one-on-one meetings with your manager.
• Access to mentorship networking opportunities including access to Asian, Hispanic / Latinx, African American, women, LGBTQ, Veteran and disability-focused Business Resource Groups
• Access to learning content on Degreed and other informational platforms

About MassMutual

We’ve been around since 1851. During our history, we’ve helped millions of people find financial freedom, offer financial protection, and plan for the future.

Today, we continue to develop meaningful relationships with our customers by building their trust, being knowledge problem solvers and always prioritizing their needs.

MassMutual is guided by a single purpose : We help people secure their future and protect the ones they love. As a company owned by our policyowners, we are defined by mutuality and our vision to put customers first.

It’s more than our company structure it’s our way of life.

J-18808-Ljbffr