Job Overview
Senior AI Credit Analytics Engineer – Predictive Lending & Dynamic Risk Modelling for Consumer Credit (Qatar Market Focus)
Location: Remote – preference for candidates familiar with Qatar’s consumer finance and credit scoring landscape
Sector: Fintech – AI/ML Credit Modeling, Alternative Lending, Behavioral Analytics, BNPL Risk Engines
Employment Type: Full-Time, Remote
Language: English (Arabic useful)
Role Description:
We are seeking a Senior AI Credit Analytics Engineer to develop and deploy the next frontier of data-driven consumer credit intelligence for the Qatari market. This role is critical for creating alternative credit scoring models in a region where thin-file borrowers, informal income sources, and delayed digital adoption have traditionally hindered access to fair consumer financing.
The successful candidate will drive the end-to-end ML architecture behind lending APIs, behavioral scoring, BNPL engines, and cash flow underwriting—tailored specifically to Qatar’s regulatory expectations and financial data availability under QCB (Qatar Central Bank) governance.
Primary Responsibilities:
🧠 AI/ML Credit Models
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Build, test, and deploy custom machine learning models that assess creditworthiness using alternative datasets: telco usage, utility bills, rental payments, and social behavior proxies.
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Develop explainable AI (XAI) models to ensure regulatory transparency in lending decisions.
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Incorporate reinforcement learning mechanisms for real-time credit limit adjustment and dynamic interest optimization.
📉 BNPL Risk & Delinquency Frameworks
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Architect fraud-resistant BNPL engines with repayment propensity models, debt saturation scoring, and overdue behavior forecasts.
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Build APIs to integrate risk engines with consumer wallets, e-commerce checkout platforms, and digital banks.
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Apply graph theory and network intelligence to detect collusive lending abuse and synthetic identity clusters.
🧾 Regulatory & Ethical AI Alignment
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Ensure model auditability in line with Qatar Central Bank’s guidelines on fair lending, discrimination risk, and adverse action explanation.
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Conduct regular bias audits and fairness testing across Qatari demographics—especially migrant worker groups and students.
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Collaborate with Qatari regulatory sandboxes or innovation labs on ethics-first AI governance frameworks.
📊 Data Pipelines, API Exposure & Client Tooling
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Build real-time data ingestion systems for streaming borrower behavior, financial transaction metadata, and device signatures.
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Develop pre-built scoring APIs and dashboard interfaces for fintech partners, lenders, and microfinance providers in Qatar.
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Optimize edge deployments for real-time lending decisions via mobile apps and embedded finance contexts.
Ideal Qualifications:
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6+ years of experience in AI/ML model development, preferably in financial services, credit scoring, or alternative lending.
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Fluency in Python, TensorFlow, or PyTorch, with deep knowledge of XGBoost, LightGBM, and SHAP/LIME libraries for explainability.
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Experience working with limited data environments and deploying models in regulated fintech contexts.
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Familiarity with the Qatari financial ecosystem, QCB rules, or regional credit bureaus is strongly preferred.
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Comfort with graph databases, event-driven architectures, and production-grade ML ops.
Are you excited about this opportunity?
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