This staff position is expected to be able, under minimal supervision, conducts advanced research, data gathering, and analyses in support of more senior team members tasked with managing the duties of the Corporate Treasury ALM-Management Information System (ALM-MIS) Application and Architecture Team. One of a number of teams under Corporate Treasury ALM-MIS. Team supports the logic and data research responsibilities of the Asset/Liability Management Information System (ALMIS) database and the flow of ALMIS data into its associated analytic and reporting applications. These platforms are QRM, the Company's primary cash flow calculation, analysis and reporting engine used in a number of Corporate Treasury and Finance function, and Axiom an application that supports strategic liquidity reporting for the Company, including the production of the daily FR 2052a report. The successful candidate will have a foundational knowledge spanning the range of Finance, Treasury, and balance sheet categories. The candidate has experience in categories such as Liquidity, Deposit Liabilities, and other Balance Sheet data. The position is expected to gain facility for using the ALM-MIS owned data set managed through the ALMIS (Asset-Liability Management Information System) platform. The staff member may provide support for the input on data quality issues into development of the ALM policy and strategy in alignment with Corporate guidance, and regulatory requirements. In addition, this position will participate in data logic and attribute research to support audit and regulatory question associated with ALMIS data. This data research will also be used to onboard, configure, and test new applications, data sources. Also to enhance or reconfigure established data feeds as part of an agile continuous improvement of the ALMIS ecosystem. The staff position takes direction from a senior member of the team that manages ALM-MIS APPLICation and Architecture to support, when required. To assist other ALM-MIS teams as either a temporary part multiteam project execution groups'. The team member will through research effort collect financial data to improve basic governance processes and reports used to manage the data quality in the ALMIS-AXIOM-QRM ecosystem. This research will also be used to improve or build new processes and reports measuring the validity and accuracy, reporting on unexpected/undesired results; or contribute to remediation but may require collaboration with senior staff to determine a solution. Escalates unprecedented and complex issues to more senior team members/management.
The staff member will be expected to cultivate relationships with staff or contractors in: Corporate Technology, the Finance Data Strategy/Data Stewards, Data Operations, Risk Management, Finance Liquidity Regulatory Reporting and Corporate Treasury to ensure efficient identification, collection, and use of ALMIS data along with the management of the associated data governance processes. The staff member provides supporting documentation and analyses for management reports/briefings. The staff member's research effort will participate in and may help coordinate application upgrades or ALMIS platform change control and associated testing/validation processes. Reviews work with more senior professionals to improve own work. Bachelor's degree or the equivalent combination of education and experience is required. Degree in math, engineering, statistics, computational finance or economics preferred. MBA, CFA, or CPA/CA preferred. 5-7 years of total work experience preferred. Experience with balance sheet data, its use, governance and management, and related data in any of the following: liquidity analytics and reporting; liquidity stress testing; liquidity risk management, or asset-liability management within large complex financial organizations is strongly preferred. Experience with Relational, Non-relational Database Structures, Business Intelligence data management and visualization applications (such as Power BI) and the ability to use SQL (or other computer languages such as python) for data analysis is a plus.