Who we are looking for

A strong credit risk analytics person to join the Credit Risk Management Group within Enterprise Risk Management’s Financial Risk Organization as Officer based in Hangzhou, China.

Why this role is important to us

The team you will be joining plays an important role in the overall success of the organization. Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. To make that happen we need teams like yours to help navigate employees and the organization as a whole. In your role you will strive for cutting-edge solutions, that are straightforward and scalable. You will help us build resilience and execute day to day deliverables at our best. Join us if making your mark in the financial services industry from day one is a challenge you are up for.

What you will be responsible for

As Credit Risk Analytics Officer you will:

Work with credit risk modelers from Centralized Modeling, Analytics, and Operations Group (CMAO) to develop or enhance credit risk models (e.g., PD/LGD/EAD) used in critical risk management processes such as CECL/BASEL/CCAR/Quarterly Stress Testing.Review and verify model assumptions and limitations with credit risk modelers.Perform model executions for various risk management processes and conduct output analysis by working with credit risk modelers, credit risk experts, and economists to ensure results align with given economic scenarios and portfolio characteristics.Conduct sensitivity analysis to evaluate the impact on credit risk metric or model output to variations in key inputs; draw meaningful conclusions on the robustness of credit risk tools in relation to intended usage scenarios.Conduct attribution analysis to identify and quantify the impact of factors (e.g., scenarios, portfolio composition, model overlays) on observed or forecasted outcomes.Work with the credit risk team to document and present the credit risk analysis to ensure traceability and transparency.Work with the credit risk team in enhancing automation within sub-processes to improve efficiency, reduce manual effort, and streamline operations.Explore the use of advanced analytics or machine learning in the process of credit risk management.

What we value

These qualities will help you succeed in this role:

Strong passion and curiosity in risk management, especially in the credit risk domain.Strong analytical and quantitative mindset; ability to take ownership and improve on existing risk models and methodologiesEnergetic/motivator: an enthusiastic individual with proven leadership skills and an ability to motivate a diverse, multi-level workforce and instill a sense of urgency on a range of evolving goals and objectivesOrganizational strengths: an ability to organize projects, processes and priorities to ensure business needs are met in a coordinated, responsive and timely manner, with minimal directionConfidence: a self-assured, experienced and knowledgeable individual able to quickly garner support for his/her views based on informed, well-presented direction or analysis, with a willingness to negotiate, and concede, when neededCommunicator: clear, confident, self-assured communication style, coupled with an ability to react and adapt to various audiences and environments without diluting effectiveness

Education & Preferred Qualifications

PhD/Master in economics/mathematics/statistics/engineering or equivalent.Undergraduate training in mathematics and probability theory (measure theory) with good knowledge of stochastic calculus is a big plus.For Master’s Degree, 2+ years of experiences of credit risk modeling/analytics for in a financial institution is required.Strong programming skills in Python/R/SQL/Power BI etc.Strong communication skills in English (in both written and oral communication).Demonstrated experiences working with model development teams, analytical library development team and technologyMotivated and fascinated in how to apply statistics and econometric methodologies to resolve credit risk modeling challenges in financial industry

State Street's Speak Up Line