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Hi, I’m Mehfooz Mehboob Alam, a data scientist with 4+ years of experience building scalable ML, deep learning, and LLM systems for fraud detection, NLP, and enterprise analytics. I thrive on turning data into actionable insights that drive business outcomes. I’m proficient with Python, Spark, Kafka, and Airflow, with hands-on experience in RAG, LangChain, LangGraph, transformers (BERT, GPT, LLaMA), and multi-agent systems. I’ve deployed production ML pipelines on AWS, Docker, Kubernetes, and FastAPI, focusing on real-time processing, model optimization, and MLOps automation.…Hi, I’m Mehfooz Mehboob Alam, a data scientist with 4+ years of experience building scalable ML, deep learning, and LLM systems for fraud detection, NLP, and enterprise analytics. I thrive on turning data into actionable insights that drive business outcomes. I’m proficient with Python, Spark, Kafka, and Airflow, with hands-on experience in RAG, LangChain, LangGraph, transformers (BERT, GPT, LLaMA), and multi-agent systems. I’ve deployed production ML pipelines on AWS, Docker, Kubernetes, and FastAPI, focusing on real-time processing, model optimization, and MLOps automation.

Mehfooz Alam

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Hi, I’m Mehfooz Mehboob Alam, a data scientist with 4+ years of experience building scalable ML, deep learning, and LLM systems for fraud detection, NLP, and enterprise analytics. I thrive on turning data into actionable insights that drive business outcomes. I’m proficient with Python, Spark, Kafka, and Airflow, with hands-on experience in RAG, LangChain, LangGraph, transformers (BERT, GPT, LLaMA), and multi-agent systems. I’ve deployed production ML pipelines on AWS, Docker, Kubernetes, and FastAPI, focusing on real-time processing, model optimization, and MLOps automation.…Hi, I’m Mehfooz Mehboob Alam, a data scientist with 4+ years of experience building scalable ML, deep learning, and LLM systems for fraud detection, NLP, and enterprise analytics. I thrive on turning data into actionable insights that drive business outcomes. I’m proficient with Python, Spark, Kafka, and Airflow, with hands-on experience in RAG, LangChain, LangGraph, transformers (BERT, GPT, LLaMA), and multi-agent systems. I’ve deployed production ML pipelines on AWS, Docker, Kubernetes, and FastAPI, focusing on real-time processing, model optimization, and MLOps automation.

Available to hire

Hi, I’m Mehfooz Mehboob Alam, a data scientist with 4+ years of experience building scalable ML, deep learning, and LLM systems for fraud detection, NLP, and enterprise analytics. I thrive on turning data into actionable insights that drive business outcomes.

I’m proficient with Python, Spark, Kafka, and Airflow, with hands-on experience in RAG, LangChain, LangGraph, transformers (BERT, GPT, LLaMA), and multi-agent systems. I’ve deployed production ML pipelines on AWS, Docker, Kubernetes, and FastAPI, focusing on real-time processing, model optimization, and MLOps automation.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

Data Scientist at Morgan Stanley

September 1, 2024 - Present

Data Scientist responsible for building a real-time fraud detection pipeline processing 3M+ transactions/day using Python, Spark Structured Streaming, and Kafka, achieving a 23% improvement in fraud capture rate with sub-second latency under production constraints. Engineered a hybrid detection system combining XGBoost, Isolation Forest, and PyTorch autoencoders to enhance anomaly detection precision by 18–25% and reduce false positives by 30% through feature optimization and dynamic thresholding. Designed high-dimensional feature engineering pipelines (velocity features, geo-behavioral patterns, device fingerprint graphs) with Spark SQL to improve model lift and stability across evolving fraud patterns. Integrated Transformer-based NLP models (BERT with domain-adapted embeddings) to analyze transaction metadata and unstructured merchant descriptions, enabling 20% gain in detection of unseen fraud patterns via semantic enrichment. Built LLM-powered fraud explanation system using Lang

Data Scientist at Accenture

January 1, 2021 - June 1, 2023

Configured a RAG-based NLP system processing 5M+ customer reviews using FAISS-based semantic retrieval, LangChain, and LL m prompting strategies, reducing manual analysis effort by 45% and accelerating product insight cycles. Developed and fine-tuned Transformer-based sentiment classification models (BERT using TensorFlow + Hugging Face), improving classification accuracy by 22% over baseline models. Implemented topic modeling pipelines (BERTopic + LDA) to extract product issue clusters and customer sentiment themes, improving product feedback resolution efficiency by 18%. Designed LLM-based summarization system using RAG pipelines and prompt optimization, reducing manual analyst workload by 45%. Built end-to-end MLOps pipelines using AWS (S3, SageMaker), Docker, and CI/CD workflows, reducing model deployment cycle time from weeks to under 24 hours with automated validation checks. Orchestrated ETL + ML workflows using Apache Airflow DAGs, enabling automated data ingestion, feature ref