State Street

Quantiative Analyst, Officer

Hangzhou, China Full time
Job Description

Who we are looking for

An experienced professional with a strong technical and quantitative aptitude to act as a Quantitative Risk Manager, Officer based in Hangzhou, China. This role will report to model validation lead in China, within Model Risk Management Department.

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 Quantitative Risk, Officer you will

  • Work with team members in Hangzhou under the supervision of the model validation lead in China, and conduct model validation activities covering SSC models worldwide:

    • Perform independent validations on models such as credit risk, market risk, climate risk, portfolio management, pricing and AI models.

    • Perform deep analysis on modelling data through applying statistical analysis or machine learning approaches.

    • Conduct quantitative analysis to verify that models are performing as expected. 

    • Streamline the existing analytical process; increase the pace of execution.

    • Communicate with model developers and business to relay the issues and feedback and capture the action plans.

What we value

These skills will help you succeed in this role

  • Strong analytical and quantitative mindset; ability to take ownership and improve on existing risk models and methodologies

  • Confidence: 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 needed

  • Communicator: 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

  • Master or PHD degree in a quantitative disciplines (e.g. Finance, Statistics, Economics, Mathematics, Computer Science / Engineering or equivalents)

  • 2+ years of experience in quantitative analytics including model development or independent model validation in a regulatory financial institution or consulting firm.

  • Demonstrated some understanding of industrial best practices of quantitative analytics in Credit Risk, or Market risk.

  • Demonstrated modeling and analytical process engineering capabilities

  • Some understanding of various regulations such as Basel, stress testing and CCAR

  • Proficient in one or more programming languages, such as SAS, R, Matlab, Python

Additional requirements

  • Ability to take initiative and meet deadlines. 

  • Finance and/or risk management certificates like CFA and FRM are preferred but not required.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

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