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Ahmad Alomari
Senior Data Scientist & Machine Learning Engineer specializing in computer vision and production ML
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About
PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.
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Key Strengths
- Built end-to-end Spark + NLP/ML pipeline for space-weather (geomagnetic storm) prediction on 5GB+ satellite logs
- Reduced sensor data errors by >80% via Spark-based validation, interpolation, and normalization
- Hybrid entity-resolution approach (rules + semantic embeddings) with threshold tuning and F1 optimization; ~20% accuracy improvement
- Fine-tuned E5 embeddings with contrastive learning and deployed in Pinecone; improved top-5 retrieval precision by 25%
- Production-grade workflow design: modular ETL/ML pipelines with Airflow orchestration, Dockerization, CI/CD, and drift/latency monitoring
- Pragmatic experimentation-to-production decision-making based on accuracy/latency targets and diminishing returns
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Experience
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Publications
4 publications
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