Operational Risk, AVP
2 months ago
Job Description
At State Street, we are dedicated to developing state-of-the-art financial technologies. Our team is seeking a visionary tech leader to innovate the design and implementation of a cutting-edge quantitative library that will revolutionize the way we analyze and process financial data. This is a unique opportunity to influence the fintech space, spearhead a dynamic team, and set new industry benchmarks. If you’re ready to unleash your technical powers and drive innovation, join us on this journey and lead the change in reshaping the future of quantitative risk analysis. The ideal candidate should have strong background in quantitative methodologies and analysis, as well as software development to lead the design and implementation of a new quantitative library from the ground up. In addition, the candidate should be a dynamic and innovative thinker with extensive experience in quantitative finance and software architecture. This role is pivotal in setting the foundation for State Street’s endeavors to strengthen the company’s risk control function.
Responsibilities :
Participant in model and algorithm design, development, and implementation using advanced numerical and computational techniques. Integrate, customize, and train well known model and algorithm in open-source libraries to solve financial market problems Develop methodologies, algorithms and diagnostic tools for testing model stability and performance. Work with a team of data scientist, machine learning engineer, financial modeler, software engineer, and model validation/QA engineer Support IT integration, QA/UAT and deployment of risk library, operationalizing and productizing resulting models and solutions Engage business risk managers, clients and other partners to present the model, technology platform and tools. Participate in the analysis and interpretation of model results incorporate partner’s feedback as appropriate into the implementation.Qualifications :
Master degree required (preferably in computer science, mathematical finance, and financial engineering) Solid background in mathematics including but not limited to statistics, probability theory, PDE, linear algebra, stochastic calculus, differential equations etc. 5+ years of solid object-oriented or functional programming and design experience, with 3+ years in python. Experience in numerical and quantitative methods, Monte Carol simulations and analyzing large and complex data sets. Past experience in developing or implementing risk models such as market risk, counterparty risk, wholesale credit risk or experience in front office pricing models. Familiar with traditional machine learning (regression, decision tree etc.) and deep learning neural network(CNN, LSTM etc.)Experience in any of the following is highly desirable:
Linux / Bash scripting, structured and unstructured data management tools (Oracle, PostgreSQL, MySQL, KDB+, Hadoop, etc.) Continuous integration & development environments and tools (GIT, Maven, Jenkins, etc.) Communication skills. The ability to communicate at the right level with all parties involved, including management and business stakeholders-
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