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Asset Liability Management Analyst

Company:
US Main
Location:
Plano, TX, 75024
Posted:
April 27, 2024
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Description:

Job Type: 12 months contract (possibility of extension or potentially to convert full-time as well) Overtime: As per business needs Project Summary: The primary responsibility of this role is to provide critical thought-leadership using data and analytics on Interest Rate Risk (IRR), Liquidity Risk, Funds Transfer Pricing (FTP), Valuation, and Financial Forecasting utilizing measures such as Net Interest Income (NII), Earnings at Risk (EAR), Economic Value of Equity (EVE), and other Key Risk Indicators.

The candidate will help maintain and automate financial analytical reports and dashboards with deep understanding of data and databases.

Responsibilities: Develop complex financial Asset Liability Management (ALM) models in Empyrean/ Excel/SQL to be used as the primary source for TMCC/TFSB/Other AOR SFC Asset/Liability Management program.

Develop, maintain, and grow automated processes leveraging Excel, VBA, Tableau, Power BI, python, Snowflake, .Net, C# etc.

Advise finance subsidiaries on treasury management activities, practices and procedures ensuring compliance with policies and guidelines and review and provide input on funding forecasts and associated funding programs Provide analytical support for management forums including Asset/Liability Committee (ALCO) decisions by conducting robust and comprehensive market and financial analysis to support strategy, proposals, and market transactions.

Conduct balance sheet analysis, analyze economic impact and build ALM strategies.

Technical skills (Must Have): SQL – 1-3 years.

Excel – 3+ years (Advanced) (Complex formulas) Tableau (for ex- Building dashboards from scratch) SmartView/Essbase Experience with ALM Tools – Empyrean/Bancware/QRM (Preferred) Must Have’s: Strong treasury experience Strong ALM experience Strong financial experience (Financial modeling) Strong Exposure to fixed income finance instruments Strong in Managing financial instrumental data

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