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Ken Anderson

About

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Senior AI/ML Data Scientist | NLP & LLM Engineer | Big Data & Cloud AI Architect | MLOps & Model Deployment | Healthcare & Fintech Solutions
Arizona, United States

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Résumé


Jobs verified_user 0% verified
  • Nexus
    Lead AI/ML Data Scientist | NLP Engineer | Cloud AI Architect
    Nexus
    Apr 2024 - Current (2 years 6 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
  • Synchrony
    Senior AI/ML Data Scientist | LLM/NLP Engineer | Big Data & Cloud AI Specialist
    Synchrony
    Jun 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 GC
  • Privia Health
    AI/ML Data Scientist | NLP Specialist | Healthcare ML Engineer
    Privia Health
    Jul 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 E
  • SeatGeek
    Machine Learning Engineer | Applied Data Scientist | Infrastructure ML Lead
    SeatGeek
    Feb 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 strate
  • CERNER CORPORATION
    AI Consultant | NLP & LLM Engineer | Cloud ML Architect
    CERNER CORPORATION
    Aug 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 w
Education verified_user 0% verified
  • B
    Bachelor's degree, Computer Science
    Apr 2010 - May 2014 (4 years 2 months)