Promote and support overall analytics competency by advising business, application and operations counterpart. Provide training on available tools, with specific focus on Python, and ensure data integrity and availability. Develop strategies and processes for data implementation, data acquisition, execution, reporting and archive recovery. Resolves data integration and security issues for adherence to the organization's quality standards.Competencies include:- Utilize business processes and technologies for gathering, storing, analyzing, and providing access to data that helps the organization make better business decisions- Knowledge of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and ability to leverage that information in creating customized customer solutions- Manage architectures, data resources, polices, practices and procedures to appropriately and effectively address business and stakeholder's needs- Develop and maintain an organization's data in order to meet business requirements- Knowledge of tools, techniques and practices in data mining technologies used to acquire essential business information- Use tools, controls, techniques, established principals and standards to ascertain the quality, effectiveness, security and accuracy of information systems- Utilize a variety of administrative skill sets and technical knowledge to manage organizational IT policies, standards, and procedures- Assess and effectively manages all of the risks associated with their business objectives and activities to ensure activities are in alignment with the bank’s and unit’s risk appetite and risk management framework- Use tools and techniques for analyzing and documenting logical relationships among data, processes or events- Use a structured approach to identify the cause of undesirable consequences in a manufacturing environment and the changes needed to prevent a recurrence

Provides independent review of model validations, effectively assessing the validity of issues raised and methodological approaches for the proper resolution of these issues. Reports regularly to the Model Risk Manager on the compliance of the model risk management program, including policies and procedures, with respect to its progress, working issues, and challenges. Develops and maintains effective partnerships with the model analysts, model owners, business level risk management teams and auditors, internal and external. Provides recommendations for the design, development, back testing, implementation and recalibration of models owned by the model development team. Assists in the review and validation of model performance and controls, including establishing the model validation scope, assessment of validation results and directing communication with stakeholders. Assists in the development and maintenance of the model inventory ensuring the inventory is complete, accurate, and consistent with the intent of the Model Validation Policy. Validation work done is intended to assist the bank in remaining compliant with the CCAR framework.

Anticipate or assess customer needs and develop mathematical and statistical algorithms for analyzing data for patterns, trends and metrics to convert data into information. Implement algorithms in C++, Python or JavaScript for client and server side processing. As Principal Investigator on the company’s first SBIR, responsible for the system functionality to the program technical requirements within cost and schedule constraints and for managing the project technical efforts required to produce the end products. General duties include providing leadership and supervision to a team of technical professionals and interns as well as applying project management practices to meet scope, schedule and budget expectations.

Model validation of credit, market and operational risk models used by the various business units, interpretation of results and the development of summaries used to communicate those results to management and other users of summaries.

Derivation, implementation, validation, documentation and delivery of mathematical models and/or computer simulations to support the designing and construction of remote sensing instruments. Examples include hyper-spectral sounders, multi-spectral imagers, LADAR/LIDAR and missile defense systems. Knowledge of Matlab, C/C++ and IDL/ENVI required. Typical projects begin with ill-posed problems requiring creative solutions. Participation at all phases, from bid to final hand-off required.

Analysis of lending software for Chase Manhattan Mortgage Corporation.