In this role, you will: Lead complex, large-scale model maintenance, optimization, and planning initiatives related to operational processes, controls, reporting, testing, implementation, and documentation Review and analyze complex multi-faceted model operations and optimization challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors Develop model processes and optimization strategies for short- and long-term objectives; support and provide insights regarding a wide array of business initiatives Make decisions in complex and multi-faceted situations requiring solid understanding of agile development Influence global assessment of model maintenance schedules inclusive of engineering, structure, and scope of review following the System Development Life Cycle process, quality, security, and compliance requirements Strategically collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals Required Qualifications: 5+ years of quantitative model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Bachelors/masters degree in engineering field like computer science, Information technology, Electrical Engineering etc. M.Sc./M.Phil. in statistics/ economics/ mathematics/ operations research engineering physics 9 - 12 years of relevant hands-on experience in model development/monitoring/validation and Implementation. Must have hands on exposure in SAS, Python, PySpark and SQL. Expert in data mining and statistical analysis. Experience in developing, validating, monitoring models. Statistical models linear regression, logistic regression, time series analysis, multivariate statistical analysis Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned Experience in model deployment, User Acceptance Testing (UAT) and model monitoring. Critical thinking and strong problem-solving skills. Ability to learn the business aspects quickly Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable Ability to multi-task and prioritize between projects Ability to work independently and as part of a team Ability to research and report on a variety of issues using problem solving skills Ability to make timely and independent judgment decisions while working in a fast-paced and results-driven environment Job Expectations: Primary role is to perform highly complex activities, advanced analytics, related to creation, validation, monitoring, implementation, documentation, articulation and defense, on-going maintenance of complex models grounded in highly statistical theory used to quantify, analyze and manage credit risks or to forecasts losses and compute capital requirements or enable decision making in business, product or other functional areas. Duties typically include implementing, validating and documenting analytical models and strategies for short and long-term objectives, performing analytical support and/or modeling, and providing well-articulated insights regarding a wide array of business initiatives. The Senior Quantitative Engineering Specialist is expected to apply predictive analytics & business knowledge in order to serve as a subject matter expert, analyst, advisor and consultant to the corporate and/or lines of business (LoB) management, such as Consumer, Commercial, Small Business Banking and Cards, with respect to modeling implementation, model validation, modeling data analytics, model performance analysis and model execution This may involve recommending advances in modeling methodologies and/or overall modeling approach/ infrastructure, high performance computing.
