K
Ken Anderson
About
Detail
Senior AI/ML Data Scientist | NLP & LLM Engineer | Big Data & Cloud AI Architect | MLOps & Model Deployment | Healthcare & Fintech Solutions
Arizona, United States
Résumé
Jobs
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Lead AI/ML Data Scientist | NLP Engineer | Cloud AI ArchitectNexusApr 2024 - Current (2 years 3 months)• Architected and implemented AI-powered solutions for large-scale enterprise applications across healthcare, fintech, and e-commerce, focusing on predictive analytics, automation, and cloud integration. • Led the design and deployment of scalable cloud-based AI architectures using AWS, Azure, and Google Cloud, optimizing for performance, cost, and reliability. • Developed data pipelines for real-time analytics using Apache Spark, Kafka, and Airflow, processing millions of records daily to support mission-critical business operations. • Delivered end-to-end MLOps solutions, automating model deployment, monitoring, and retraining workflows with MLflow, Kubernetes (AKS), and Docker, ensuring smooth operations and minimal dow- Senior AI/ML Data Scientist | LLM/NLP Engineer | Big Data & Cloud AI SpecialistSynchronyJun 2021 - Mar 2024 (2 years 10 months)• Designed and productionized robust ML systems for credit risk, fraud detection, and segmentation using scikit-learn, XGBoost, LightGBM, and TensorFlow, with deployment APIs built using FastAPI and Flask. • Developed multiple LLM-based apps utilizing GPT-4, LangChain, and fine-tuned BERT via Hugging Face Transformers; integrated Prompt Engineering and LLM safety validation. • Implemented semantic vector search using pgvector, FAISS, and PostgreSQL to support financial document retrieval with NLP. • Engineered scalable big data pipelines with Apache Spark, Apache Kafka, Airflow, and dbt, processing over 10M daily records. • Managed full ML lifecycle with MLflow, DVC, and deployed models on AWS SageMaker, Azure ML, and GCP Vertex AI using Do
- AI/ML Data Scientist | NLP Specialist | Healthcare ML EngineerPrivia HealthJul 2019 - Mar 2021 (1 year 9 months)• Developed risk prediction models for readmission and chronic illness using LightGBM, Random Forest, and Bayesian optimization, delivered via FastAPI endpoints. • Engineered NLP pipelines for ICD code extraction using spaCy, NLTK, and fine-tuned BERT, integrated with LangChain and OpenAI API for experimentation. • Standardized multi-source healthcare data using Airflow, Azure Data Factory, and ETL pipelines, transforming into analytics-ready formats with Pandas and NumPy. • Containerized deployments using Docker, orchestrated via AKS with GPU support, and managed configurations with Terraform and Helm. • Automated model retraining with MLflow, versioned datasets using DVC, and validated pipelines with Pytest and Great Expectations. • Tuned
- Machine Learning Engineer | Applied Data Scientist | Infrastructure ML LeadSeatGeekFeb 2017 - Sep 2019 (2 years 8 months)• Built real-time recommendation engines using TensorFlow, PyTorch, and LSTM architectures, deployed using FastAPI. • Processed user interaction data at scale with Apache Spark, Kafka, and Airflow, and conducted feature engineering with Pandas and NumPy. • Managed versioned pipelines with MLflow, monitored deployments with Prometheus, and enabled auto-validation via GitHub Actions and Jenkins. • Built infrastructure with Terraform, deployed models to AWS ECS, and secured systems with secrets managed through AWS Secrets Manager. • Developed user embeddings and batch inference pipelines with joblib; built feature importance tools using SHAP and permutation metrics. • Supported A/B testing and rollback strategies with DVC, Pytest, an
- AI Consultant | NLP & LLM Engineer | Cloud ML ArchitectCERNER CORPORATIONAug 2012 - May 2014 (1 year 10 months)• Designed NLP/LLM solutions for summarization and triage using GPT-3, T5, BERT, and Hugging Face Transformers, with structured prompt evaluation metrics. • Deployed inference systems on Azure ML, GCP Vertex AI, and Docker containers with Flask and FastAPI as microservices. • Built secure vector search systems with pgvector, FAISS, and integrated Streamlit dashboards for internal reviews and clinician feedback, ensuring a user-friendly interface that enhances clinician interaction with AI tools. • Created CI/CD workflows using GitLab CI, provisioned cross-cloud infrastructure with Terraform, and monitored drift via Prometheus. • Validated sensitive clinical data using Great Expectations, enforced schema constraints with
Education
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- BBachelor's degree, Computer ScienceApr 2010 - May 2014 (4 years 2 months)