Senior Asset Liability Modeling Specialist

Green Horse Energy; Abu Dhabi; Remote; AED 180,000 - 240,000; Full time

Benefits offered by this job

Fully remote

Job summary

Green Horse Energy is seeking a Senior Asset Liability Modeling Specialist to develop and maintain ALM models evaluating balance sheet risks, interest rate sensitivity, liquidity, and long-term financial stability. The role collaborates with treasury, finance, actuarial, investment, and risk teams to improve modeling accuracy and governance.

The candidate will lead model development, validation, and stress testing, with a focus on data quality, governance, and actionable management insights in a

Qualifications

• Bachelor's degree in Finance, Economics, Mathematics, Statistics, Actuarial Science, Financial Engineering, or related discipline. A master's is advantageous.
• Professional qualifications such as CFA, FRM, PRM, actuarial credentials, or equivalent are preferred.
• Significant experience in asset-liability management, balance sheet risk, quantitative modeling, treasury risk, or financial risk analytics.
• Strong understanding of ALM principles, interest rate risk, liquidity risk, balance sheet dynamics, and cash flows.

Responsibilities

• ALM model development: develop, maintain, and validate quantitative models of assets and liabilities, cash flows, and funding.
• Interest rate risk modeling: analyze risk in the banking book and projected NII under rate scenarios.
• Balance sheet analysis: evaluate structures, maturities, repricing, duration gaps, and concentration risk.
• Cash flow projection: build models with contractual payments, prepayments, reinvestment assumptions, and runoff.
• Scenario analysis and stress testing: design and run storms in rates, liquidity, and funding costs.
• Behavioral modeling: develop assumptions for non-maturity deposits, withdrawals, prepayments, and redemptions.
• Liquidity and funding analysis: assess gaps, liquidity profiles, encumbrance, and stressed funding needs.
• Model calibration and validation: calibrate parameters, test against history, assess performance, investigate deviations.
• Risk measurement: compute duration, convexity, repricing gaps, earnings sensitivity, and other ALM risk metrics.
• Data quality and integrity: validate inputs, reconcile data, investigate anomalies, ensure traceability.
• Risk reporting: prepare ALM reports, sensitivity analyses, scenario results, and dashboards.

Job description

Job Title: Senior Asset Liability Modeling Specialist

Location: UAE (Remote)

Employment Type: Full-Time

Level: Senior

Work Arrangement: Fully Remote

About Us

We are seeking an experienced Senior Asset Liability Modeling Specialist to develop, maintain, and enhance asset-liability management (ALM) models used to evaluate balance sheet risks, interest rate sensitivity, liquidity positions, and long-term financial stability.

This role is responsible for analyzing the relationship between assets and liabilities, assessing potential impacts from changing market conditions, and providing quantitative insights to support strategic financial planning and risk management. The successful candidate will collaborate with treasury, finance, actuarial, investment, and risk management teams to improve modeling accuracy, strengthen risk controls, and support informed management decisions.

Key Responsibilities

• ALM Model Development: Develop, maintain, and validate quantitative models to assess the interaction between assets, liabilities, cash flows, and funding requirements.
• Interest Rate Risk Modeling: Analyze interest rate risk in the banking book and other relevant portfolios, including changes in economic value and projected net interest income under different rate scenarios.
• Balance Sheet Analysis: Evaluate asset and liability structures, maturity profiles, repricing characteristics, duration gaps, and concentration risks.
• Cash Flow Projection: Build cash flow models incorporating contractual payments, expected prepayments, reinvestment assumptions, liability runoff, and other behavioral factors.
• Scenario Analysis and Stress Testing: Design and execute scenarios covering interest rate shocks, yield curve movements, liquidity stress, funding cost changes, and adverse market conditions.
• Behavioral Modeling: Develop and review assumptions relating to non-maturity deposits, customer withdrawals, loan prepayments, early redemptions, and other behavioral cash flow characteristics where applicable.
• Liquidity and Funding Analysis: Assess funding gaps, liquidity profiles, asset encumbrance, contingency funding needs, and the impact of stressed market conditions.
• Model Calibration and Validation: Calibrate model parameters, test assumptions against historical observations, assess model performance, and investigate deviations between projected and actual outcomes.
• Risk Measurement: Calculate and interpret duration, convexity, repricing gaps, economic value sensitivity, earnings sensitivity, and other relevant ALM risk metrics.
• Data Quality and Integrity: Validate data inputs, reconcile source information, investigate anomalies, and ensure that model outputs are reliable and traceable.
• Risk Reporting: Prepare ALM reports, sensitivity analyses, scenario results, and management dashboards for senior management and relevant governance committees.
• Policy and Regulatory Support: Support compliance with applicable ALM policies, risk limits, model governance standards, and relevant regulatory requirements.
• Model Governance: Maintain model documentation, assumptions registers, validation evidence, change controls, and audit trails.
• Strategic Decision Support: Provide quantitative analysis to support balance sheet planning, investment allocation, funding strategies, and risk-adjusted decision-making.
• Process Automation: Improve modeling workflows, reporting processes, data pipelines, and analytical tools to enhance efficiency and reduce manual errors.
• Stakeholder Collaboration: Work with treasury, finance, market risk, liquidity risk, investment teams, and technology specialists to address complex modeling requirements.
• Technical Leadership: Review analytical work, guide junior team members, and promote consistent modeling practices and sound quantitative judgment.

Qualifications and Experience

• Bachelor's degree in Finance, Economics, Mathematics, Statistics, Actuarial Science, Financial Engineering, or a related discipline. A master's degree is advantageous.
• Professional qualifications such as CFA, FRM, PRM, actuarial credentials, or equivalent qualifications are preferred.
• Significant experience in asset-liability management, balance sheet risk, quantitative modeling, treasury risk, or financial risk analytics.
• Strong understanding of ALM principles, interest rate risk, liquidity risk, balance sheet dynamics, and financial instrument cash flows.
• Experience developing quantitative models for interest rate sensitivity, earnings projections, duration analysis, and scenario-based risk assessment.
• Knowledge of yield curves, discounting methodologies, repricing structures, behavioral assumptions, and financial forecasting techniques.
• Familiarity with banking or insurance balance sheets is advantageous, depending on the organization's business model.
• Understanding of relevant ALM regulatory frameworks and risk management standards, such as applicable Basel requirements for banking institutions or applicable solvency requirements for insurers.
• Proficiency in Microsoft Excel and experience with quantitative tools such as Python, R, SQL, MATLAB, or comparable modeling platforms.
• Experience with financial databases, treasury management systems, ALM platforms, or business intelligence tools is preferred.
• Strong analytical and statistical skills, including sensitivity analysis, model calibration, and interpretation of complex quantitative outputs.
• Ability to assess model limitations, challenge assumptions, and communicate technical findings clearly to non-technical stakeholders.
• Excellent written and verbal communication skills, with strong documentation and presentation capabilities.
• Ability to manage multiple modeling assignments and reporting deadlines in a remote working environment.
• High standards of integrity, accuracy, confidentiality, and professional accountability.

Key Performance Indicators (KPIs)

Performance will be assessed using measurable indicators, including:

• Model Accuracy: Reliability of projected cash flows, interest rate sensitivities, and other ALM outputs against agreed validation criteria.
• Forecasting Performance: Variance between projected and actual balance sheet movements, earnings, and cash flows where applicable.
• Model Validation Quality: Timeliness and effectiveness of model testing, calibration, validation, and remediation activities.
• Risk Identification: Effectiveness in identifying interest rate exposures, liquidity gaps, repricing mismatches, and emerging balance sheet risks.
• Scenario Analysis Quality: Accuracy, completeness, and relevance of stress testing and sensitivity analysis.
• Reporting Timeliness: Delivery of ALM reports and management analysis within established deadlines.
• Data Quality: Completeness, consistency, and accuracy of data used in model calculations and reporting.
• Model Governance Compliance: Adherence to documentation, validation, approval, and change management requirements.
• Control Effectiveness: Reduction in model errors, data discrepancies, and unresolved validation findings.
• Process Efficiency: Reduction in manual modeling tasks and improvements in model execution and reporting turnaround times.
• Stakeholder Support: Quality and usefulness of analytical insights provided to treasury, finance, investment, and risk management teams.
• Continuous Improvement: Successful implementation of enhanced modeling techniques, automation, and analytical controls.

What We Offer

• Competitive compensation aligned with experience and technical expertise.
• A fully remote working arrangement, subject to applicable employment and work authorization requirements.
• Opportunities to work on complex balance sheet risk, financial modeling, and strategic risk management initiatives.
• Professional development in ALM, quantitative finance, and financial risk analytics.
• A collaborative environment that values analytical rigor, sound judgment, and continuous improvement.
• Opportunities to contribute to modeling innovation, risk governance, and financial decision-support processes.