Darrick J. Elmore
Junior Data Scientist / AI Engineer | Python ML Developer | RAG Applications
Virginia Beach, VA | LinkedIn | GitHub
PROFESSIONAL SUMMARY
Junior Data Scientist / AI Engineer candidate with a strong IT production-support background and hands-on portfolio projects in supervised
machine learning, API-based inference, MLOps workflows, and retrieval-augmented generation. Currently completing a B.A. in Data Science
with a concentration in AI and Machine Learning while building deployable projects using Python, Pandas, scikit-learn, FastAPI, MLflow,
Docker, GitHub Actions, Streamlit, FAISS, and Pytest. Brings practical experience troubleshooting real systems, documenting solutions, and
building reliable technical workflows from development through deployment.
TECHNICAL SKILLS
Data Science / ML: Python, Pandas, scikit-learn, classification, regression, feature preparation, model evaluation, train/test workflows
AI Applications: RAG workflows, semantic search, FAISS vector indexing, document chunking, context retrieval, Streamlit AI apps
Production ML: FastAPI inference APIs, Pydantic validation, MLflow experiment tracking, Joblib model artifacts, Docker, GitHub Actions CI
Testing / Engineering: Pytest, API tests, structured logging, error handling, reproducible environments, Git/GitHub
Systems Foundation: SQL, MongoDB, Microsoft Server, Active Directory, Exchange, SharePoint, VPN, LAN/WAN, production incident
support
PROJECTS
Customer Churn Prediction API | Python, FastAPI, scikit-learn, Pandas, Pydantic, Pytest, Docker
GitHub: github.com/delmore13/customer-churn-prediction-api
Built a supervised ML classification project that predicts customer churn probability and returns a clear churn-risk category for downstream
use.
Implemented API-based model inference with FastAPI, Pydantic validation, health checks, single prediction, and batch CSV scoring
endpoints.
Serialized the trained scikit-learn model with Joblib and separated prediction logic into a clean service-layer architecture.
Added automated tests, structured logging, Docker support, GitHub Actions CI, and professional GitHub documentation.
House Price MLOps Pipeline | Python, Pandas, scikit-learn, MLflow, FastAPI, Streamlit, Docker
GitHub: github.com/delmore13/house-price-mlops-pipeline
Built a regression-focused ML pipeline for California housing data, covering ingestion, preprocessing, training, evaluation, model artifact
creation, and inference.
Used MLflow to track experiments and compare Linear Regression, Random Forest, and Gradient Boosting models across MAE, RMSE,
and R2.
Selected Random Forest as the best model with R2 of 0.8051 and exposed predictions through a FastAPI service and Streamlit
dashboard.
Added Docker, GitHub Actions CI, 7 passing tests, screenshots, CI badge, and reproducible project documentation.
Rental Document RAG Assistant | Python, FastAPI, Streamlit, FAISS, RAG, Semantic Search, Docker
GitHub: github.com/delmore13/rental-document-rag-assistant
Built a RAG-style AI assistant that retrieves relevant lease/document context and generates answers to rental document questions.
Implemented document chunking, semantic retrieval with FAISS, backend question-answering endpoint, and Streamlit user interface.
Added sample lease data, 16 passing tests, Docker/docker-compose support, .env.example, screenshots, and clean README
documentation.
Demonstrated practical AI engineering skills across vector search, retrieval workflows, API design, testing, and deployable app packaging.
PROFESSIONAL EXPERIENCE
Systems Engineer | DC Primary Care Association | Aug 2016 - Feb 2021
Provided 24-hour technical and application support across 8 nonprofit healthcare practices, supporting EMR, server, access, network, and
end-user issues in production environments.
Resolved Autotask tickets for eClinicalWorks EMR issues including provider permissions, billing claims, password resets, missing
appointments, eHX access, patient profile configurations, and Tomcat/Apache server problems.
Partnered with SQL development and vendor teams to troubleshoot bugs, support testing across production/test environments, and assist
with after-hours SQL server upgrades and patch implementations.
Improved support reliability through incident documentation, vendor coordination, user communication, and hands-on troubleshooting
across healthcare technology systems.
Technical Support | Department of State | Oct 2014 - Mar 2016
Supported the Department of State as a federal IT contractor on the Network Operations Team, resolving access, account, software, and
network support requests.
Troubleshot ASP.NET, IIS, Active Directory, Microsoft Office, CAC card, file permission, phone setup, and classified/unclassified system
access issues using UTT ticketing workflows.
Systems Administrator | SRI International | Jan 2013 - Apr 2014
Rebuilt and supported network infrastructure including VLAN configuration, Group Policy permissions, Exchange, Active Directory,
hardware/software support, and application troubleshooting.
Installed, analyzed, modified, stress-tested, debugged, and supported application systems for research developers and visiting
government/NATO dignitaries.
EDUCATION & CERTIFICATIONS
B.A. in Data Science, Concentration in Artificial Intelligence and Machine Learning - Expected March 2027
A.S. in Computer Science, Grantham University - 2024
Data Engineer Certification, University of Chicago - 2021
Additional IT certifications: A+, Network+, Linux+, MC