ABA BankHead OfficeActive opening

ABA Bank

Credit Risk Analyst

Banking/FinancePosted 1 d ago

Location

Head Office

Job Type

FULLTIME

Experience

2+ Years

Level

Mid

Work Mode

On-site

Industry

Banking/Finance

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About the role

Leverage advanced credit risk analytics, Expected Credit Loss (ECL) modelling support, and programming-based data analysis (Python / R) within the Credit Risk and Analysis Department to deliver high-quality insights that support credit risk monitoring, IFRS 9 compliance, and strategic portfolio decision-making.
Integrate statistical analysis, automation, and visualization technologies to convert large and complex credit datasets into actionable intelligence for management, regulators, and stakeholders.
Design, develop, and maintain advanced Power BI dashboards covering: Credit portfolio composition and concentration risk, Asset quality and delinquency metrics, ECL metrics (Stage allocation, PD, LGD, EAD, overlays).
Enhance dashboards by embedding outputs generated from Python or R analytics pipelines.
Optimize DAX measures, data models, and performance for large-scale credit datasets.
Conduct sophisticated analysis using Python and/or R, including: Credit migration and roll-rate analysis, Vintage analysis and cohort tracking, Stress testing and scenario analysis, Sensitivity, simulation and impact analysis on ECL, and other related credit risk reports.
Support ECL model monitoring by performing trend and back-testing analysis, and identifying model drift, outliers, and unusual behaviours from ECL model data.
Apply statistical and analytical techniques such as: Regression analysis, Probability distributions, Time-series analysis.
Document methodologies and analytical assumptions clearly to ensure auditability.
Build and maintain automated data pipelines using: Python (pandas, numpy, scipy, matplotlib, seaborn) and R (tidyverse, data.table, ggplot2).
Integrate data from: Core banking systems, Credit systems, ECL model platforms, and External macroeconomic datasets (when applicable).
Design and maintain ETL flows using: Power Query and Python or R scripts.
Reduce manual Excel-based processes by replacing them with reproducible code-based analytics.
Implement data validation, reconciliation, and version control to ensure accuracy and reliability.
Continuously enhance expertise in: Python and R for financial and risk analytics, Credit risk and ECL methodologies, and Data visualization and automation tools.
Explore emerging analytics techniques (e.g., machine learning applications for credit risk where applicable).

Requirements

Bachelor’s degree in finance, Accounting, Information System and/or other related fields is required.
Minimum two years of experiences in Finance, Accounting, and Analytics, preferably in financial services.
Strong proficiency in Python and/or R for data analysis and automation.
Hands-on experience with pandas, numpy, scipy, matplotlib, seaborn (Python), tidyverse, data.table, ggplot2 (R).
Advanced skills in: Power BI (DAX, data modelling, performance optimization), Power Query, SQL.
Strong understanding of Credit risk fundamentals, IFRS 9 / ECL concepts, Loan portfolios and asset quality metrics.
Experience developing executive-level dashboards and analytical reports.

Required Skills

FinanceAccountingInformation SystemAnalyticsPythonpandasnumpyscipymatplotlibseaborntidyversedata.tableggplot2Power BIDAXData ModellingPerformance OptimizationPower QuerySQLCredit risk fundamentals

About ABA Bank

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