Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Information Technology, or a related field.
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Master’s degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Mathematics, Applied Mathematics, Econometrics, or a related quantitative field. A Bachelor’s degree in the above fields with substantial relevant professional experience may also be considered.
Professional certifications in Data Science, Machine Learning, Artificial Intelligence, Data Analytics, Cloud Computing, or Business Intelligence are an advantage.
At least five (5) years of relevant professional experience in data science, machine learning, advanced analytics, statistical modeling, artificial intelligence, or predictive analytics.
Demonstrated practical experience in designing, developing, training, validating, and deploying machine learning models and data-driven solutions to address complex business and operational challenges.
Strong knowledge of statistical analysis, probability, predictive modeling, data mining, hypothesis testing, forecasting, and advanced analytical techniques.
Proven experience using programming languages and data science frameworks, particularly Python and SQL,
Demonstrated experience in the design, development, configuration, and implementation of Credit Scoring Engines, including the development of statistical and machine learning-based credit scoring models for automated borrower risk assessment and credit decision-making.
Proven experience developing credit scoring methodologies using customer demographics, financial information, income, savings, repayment behavior, credit history, transaction patterns, business performance, and alternative data sources.
Experience developing, calibrating, validating, and optimizing credit scorecards and risk models, including application scoring, behavioral scoring, probability of default (PD), risk segmentation, and borrower risk classification.
Strong understanding of credit risk assessment methodologies, score thresholds, risk grading, loan eligibility criteria, affordability assessment, and automated credit decision rules.
Experience integrating Credit Score Engines with Core Banking Systems, digital lending platforms, customer information systems, external data sources, and API-based decision-making services.
After checking the eligibility criteria and preparing all the necessary documents, qualified and eligible applicants shall apply only online through hrtalent2027@gmail.com. within 7(seven) days from the date of this announcement.
Note: Please indicate the job title in the email subject line and submit all testimonials as a single PDF file.
Application deadline: 5:00 PM, Nov 20, 2026.
