Results-driven Data Scientist with 4 years of experience delivering high-impact AI and machine learning solutions within large-scale
enterprise environments, particularly in healthcare analytics. Proven track record of b…
Results-driven Data Scientist with 4 years of experience delivering high-impact AI and machine learning solutions within large-scale
enterprise environments, particularly in healthcare analytics. Proven track record of building and deploying end-to-end ML systems,
LLM-powered applications, and RAG-based intelligent platforms that drive measurable business outcomes, including $30M+ projected
savings and $3M+ realized cost optimization. Specialized in Generative AI, NLP , transformer models, and scalable ML infrastructure, with
hands-on expertise in fine-tuning LLMs, knowledge distillation, and deploying production-grade AI systems using cloud and
containerized environments. Recognized for strong ownership, cross-functional collaboration, and the ability to translate complex data
problems into scalable business solutions. Consistently rated as a top performer, with multiple awards for innovation and impact.
Actively seeking Data Scientist / AI Engineer / ML Engineer roles in UAE, bringing global enterprise experience and a strong foundation in
building AI-driven products aligned with business goals.
<p>BioMistral – Medical Document Classification</p><ul><li>$3M+ annual cost savings delivered by building 22 HCC classification models that replaced external vendor dependency</li><li>50,000 documents daily (1M+ pages) processed through fine-tuned BioMistral-7B using QLoRA with 4-bit quantisation</li><li>8% precision improvement (52% → 60%) across 40 Hierarchical Condition Category groups, outperforming legacy models</li><li>5x inference acceleration achieved through TinyBERT knowledge distillation, reducing processing from 2.5 hours to 30 minutes</li><li>80% GPU cost reduction by migrating from A100 to T4 hardware while maintaining model performance</li></ul><p></p><p>ClaimBot – RAG-Based Claims Intelligence Assistant</p><ul><li>Built from scratch a production-grade RAG system now serving 250 daily users across claims operations</li><li>700+ weekly queries handled with 67% user satisfaction rate, reducing SME dependency for claims adjudication</li><li>2,200 pages indexed using hybrid semantic + keyword retrieval via Azure AI Search</li><li>OpenAI reasoning models integrated to deliver structured, explainable responses for complex insurance queries</li></ul><p></p><p>MSK Affordability – Predictive Health Deterioration</p><ul><li>$30M projected annual savings enabled through predictive model identifying high-risk patients for proactive interventions</li><li>5 million patient records (232GB, 2021–2023) analysed to identify cost drivers for hip, knee, and shoulder replacements</li><li>11% precision improvement (17% → 28%) in health deterioration prediction for 50,000+ high-risk members</li></ul>
<p>VIVO - Scalable Call Analytics & Agent Performance Platform Objective:</p><ul><li> Build a scalable system to evaluate call center agent performance and improve operational efficiency.</li><li>Played a key role in scaling the platform from 20K to 1M+ calls per day (50x growth) within a short span of 3 months.</li><li>Designed and implemented machine learning models to evaluate agent performance, replacing heuristic-based systems with more</li></ul><p>scalable solutions.</p><ul><li>Developed a Call Closing Effectiveness algorithm to quantify agent behavior and improve quality monitoring processes.</li><li>Engineered fault-tolerant ETL pipelines (7+) using Apache Airflow, ensuring seamless data flow across multiple business units.</li><li>Leveraged Kubernetes (horizontal & vertical pod autoscaling) to optimize system performance, achieving 200-300% improvement in</li></ul><p>throughput.</p><ul><li>Built monitoring dashboards using Grafana, enabling real-time tracking of system health and performance.</li><li>Worked closely with product managers, engineering teams, and business stakeholders to continuously refine system capabilities.</li><li>Business Impact:</li><li>Enhanced call center productivity and decision-making</li><li>Enabled scalable performance evaluation across 400+ agents</li><li>Improved system reliability and reduced processing bottlenecks</li></ul>
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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