I lead a 6-person AI/ML team at Askari Bank, shipping GenAI chatbots, risk analytics, and automation across 9 departments — serving 6,000 employees and 1.3 million customers. My path here went through cancer genomics, computational biology, and consulting. The same skills that find signal in noisy biological data build explainable models in regulated banking.
From a solo data scientist to a full AI/ML unit — building intelligence into banking operations, compliance, and customer experience.
Agentic RAG chatbots for HR (6,000 users), Islamic Banking (720 branches), IS Compliance, and Customer Service (1.2M mobile users). JSON-strict outputs with evaluation gates.
AHT ↓ 25% · 40% self-service containmentEnd-to-end pipeline reducing credit portfolio reporting from 15 days to 5 minutes. Automated data prep, BI dashboards, and risk monitoring for faster, fresher decisions.
15 days → 5 min · NPL exposure ↓ 28%ML-powered name matching and anomaly detection replacing manual spot-checks with hourly automated reviews — screening 168,000+ names daily with full coverage.
168K+ names/day · 100% coverageRedesigned the fraud detection pipeline through threshold calibration, feature engineering, and post-decision rules — cutting false-positives by 32%.
False-positives ↓ 32%Automated 20-30 daily reports across Finance, Operations, and Digital Banking. TBML variance reporting reduced from 20 minutes to under 1 minute.
875+ hours/year savedUplift modeling drove mobile banking penetration up 20% YoY. ATM predictive maintenance reduced unplanned outages by 15%, pushing availability to 97%.
Mobile ↑ 20% YoY · ATM availability 97%From computational research to commercial consulting to banking leadership — a consistent thread of applying pattern recognition to high-stakes, regulated problems.
Lead 6-person team delivering AI/ML solutions across 9 departments. Own enterprise-wide AI/ML portfolio: roadmap, delivery, and governance across risk, fraud, service, and marketing. Architect end-to-end solutions from ambiguous requirements. Shifted production stack to cloud with CI/CD and cost controls.
Hands-on coding for critical projects while providing technical guidance. Built the credit portfolio automation, NACTA monitoring, fraud detection improvements, and GenAI chatbots that became the foundation for the AI/ML unit.
Delivered production AI/ML solutions to commercial clients across finance, health tech, HR tech, and e-commerce. Highlights: AWS data lakehouse ($250K/year savings), employee retention prediction (AUC 0.91), cross-market product comparator for EU retailer.
Led applied analytics lab (4-8 researchers). Delivered 15+ funded projects with 8 production pilots for industry partners. Published 22 peer-reviewed papers. Mentored 25+ students into tech industry roles. Secured PKR 40M+ in research grants.
Research in computational biology and bioinformatics. Postdoctoral fellow (Jan–Aug 2015): ML and network analysis on biomedical data.
Research spanning cancer genomics, health informatics, and computational biology — published in Frontiers in Genetics, PeerJ, PLoS ONE, Journal of Translational Medicine, and BioMed Research International. Reviewer for Scientific Reports, BMC Medical Genomics, and others. Google Scholar →
Open to conversations about banking AI, responsible ML adoption, speaking opportunities, and collaboration.