Job
Description
In this role, you will: Perform highly complex activities related to creation, implementation, and documentation Use highly complex statistical theory to quantify, analyze and manage markets Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives Utilize structured securities and provide expertise on theory and mathematics behind the data Manage market, credit, and operational risks to forecast losses and compute capital requirements Participate in the discussion related to analytical strategies, modeling and forecasting methods Identify structure to influence global assessments, inclusive of technical, audit and market perspectives Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills Required Qualifications: 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications Eagerness to contribute collaboratively on projects and discussions and support the development of high performing teams Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions Aptitude for synthesizing data to 'form a story' and align information to contrast/compared to industry perspective. Intellectually curious, enjoys solving problems. Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Able to demonstrate first-hand knowledge of advanced topics in various mathematical and numerical methods such as linear algebra, applied probability, and statistics (Logistic regression, Time Series and Machine learning techniques); Familiarity in one or more of the following areas: Liquidity and Capital models, Stress testing models (ILST, LCR), Recovery and resolution planning models, Asset-liability risk management, Deposit models, Predictive modelling with Logistic regression, Time Series and Machine learning techniques. Strong mathematical, statistical, analytical, and computational skills along with programming experience in SQL, Python, SAS, R, and comfortable working with large datasets Strong communication skills for a variety of audiences (other technical staff, senior management, and regulators) both verbally and in writing Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions Ability to work independently on complex model validations from start to finish Attention to detail in both analytics and documentation Job Expectations Perform highly complex activities related to creation, implementation, and documentation Use highly complex statistical theory to quantify, analyze and manage markets Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives Utilize structured securities and provide expertise on theory and mathematics behind the data Manage market, credit, and operational risks to forecast losses and compute capital requirements Participate in the discussion related to analytical strategies, modeling and forecasting methods Identify structure to influence global assessments, inclusive of technical, audit and market perspectives Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills Develop benchmarking and alternative models in Python/R/Matlab/SAS Conducting model replication and review of model documentation Managing and mitigating model risk to meet or exceed regulatory and industry standards. Providing leadership and consultation to less experienced validators and business partners Communicating model risk findings and limitations to key stakeholders Contributing to the improvement of model building and model use practices Providing analytical support and offering insights regarding a wide array of business initiatives.
