Skills
Machine Learning & Statistical Modeling
Supervised & Unsupervised Learning · Predictive Modeling · Logistic Regression · Random Forest · Bayesian
Inference · Time Series Forecasting · Feature Engineering · Dimensionality Reduction (PCA) · Model Evaluation & Tuning · Model Interpretability
Deep Learning & Generative AI
Transformer Architectures · GPT-4 · Mistral · BERT · LLM Fine-tuning · Prompt Engineering · RAG (Retrieval Augmented Generation) · Conversational AI · Content Summarization · Semantic Search · NLP Fact-Checking · NLTK · SpaCy · Scikit-learn
MLOps & Productionization
End-to-End ML Pipelines · MLflow · Kubeflow · SageMaker Pipelines · CI/CD for ML · Drift Detection · Model Monitoring · Deployment Automation · Real-Time & Batch Inference
Big Data & Data Engineering
PySpark · Databricks · Spark · Snowflake · SQL/PLSQL · AWS Glue · Athena · Data Lake Architecture · ETL/ELT Workflows · Data Cleansing & Quality · Data Migration & Integration
Cloud Infrastructure & DevOps
AWS (SageMaker, EC2, Lambda, S3, DynamoDB, AppSync, Cognito, SNS, Secrets Manager, CloudFormation, SAM) · Docker · REST APIs · Serverless Architecture · Infrastructure as Code
Data Visualization & Reporting
Tableau · R Shiny · ggplot2 · Operational Reporting · Executive Presentations · Data Storytelling
Programming Languages
Python · R · SQL · Java · MATLAB · Bash/Shell
About
Seasoned Senior Data Scientist and Machine Learning Engineer with over 10 years of cross-functional experience delivering scalable AI/ML solutions across healthcare, media, federal, and telecom industries. Proven expertise in building end-to-end machine learning systems, from data pipelines and model development to MLOps and cloud deployment, using tools like AWS (SageMaker, Lambda, DynamoDB), Databricks, PySpark, and TensorFlow. Adept at leading cross-functional teams, mentoring junior talent, and translating complex business challenges into data-driven strategies. Specialized in NLP, LLMs, and Generative AI, with hands-on experience in fine-tuning models (GPT-4, BERT, Mistral), designing fact-checking and semantic search systems, and deploying production-grade Conversational AI applications. Background includes federal healthcare analytics (CMS, NIH, FDA), predictive modeling for national TV ratings, and enterprise asset lifecycle optimization. Committed to responsible AI, statistical rigor, and delivering measurable impact through innovative, ethical, and production-ready solutions.
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