OSCAR CARDEC
PROFESSIONAL SUMMARY
Lead Data Scientist combining 20+ years of national security and military leadership with 8 years of specialized experience in data science, full-stack machine learning pipelines, and Generative AI. Proven record of orchestrating cross-functional data engineering initiatives for the DoD, deploying Palantir solutions and cloud analytics ecosystems, and translating complex operational challenges into actionable decision-making tools. Active Security Clearance. Security+ Certified.
CORE COMPETENCIES
• Machine Learning: Optimization, Survival Analysis, Time-Series, Clustering, NLP, Neural Networks
• Data Analysis: Inferential Statistics, EDA, Data Engineering, Advanced Data Interface & Visualizations
• Strategic Leadership: Decision Analysis, Critical Thinking, Project Management, Mentorship
• Technical Expertise: Python, SQL, R, Scikit Learn, TensorFlow, PySpark, Palantir Foundry, Power BI
• Data Analysis: Inferential Statistics, EDA, Data Engineering, Advanced Data Interface & Visualizations
• Strategic Leadership: Decision Analysis, Critical Thinking, Project Management, Mentorship
• Technical Expertise: Python, SQL, R, Scikit Learn, TensorFlow, PySpark, Palantir Foundry, Power BI
PROFESSIONAL EXPERIENCE
Data Scientist | ManTech International Corporation (Sep 2024 – Present)
• Led data orchestration strategy/implementation; standardized Enterprise data management framework for 5500+ personnel workforce; $13.6 Million assets valuation
• Integrated Palantir Envision/Air Force talent management & promotion board tracking capability, leveraged AIP insight extraction; expedited 4 COCOMs FORGEN decision-making cycle/weapon systems
• Baselined DAF Survival Analysis model, exposed groups/targets of opportunity; sustained retention quotas for top-rated flying career fields/22,000 members
• Developed first HAF-level PowerApps consolidated framework/integrated 70+ Power BI interactive reports; synchronized secured-information across all MAJCOM/COCOMs
• Data-mined/migrated 22 million historical financial records, developed first DFAS special pay Envision Workshop application; informed HR incentive policies for ~200K military members
Data Scientist - R&D Strategist | Webworld Technologies, Inc. (Jul 2023 – Sep 2024)
• Directed Data Catalog cloud solution market analysis, advised Data Officer on multi-year/6 million contract; led Air Force first smart data-assets inventory & sustained DoD VAULTIS federal mandate
• Steered HAF/A2 Data Management implementation plan, adopted “medallion architecture”; strategized data governance framework & postured Air Force DCGS OBI production framework
Data Scientist - ML Specialist | GovCIO (Feb 2023 – Jul 2023)
• Led quantitative analysis/anomaly detection program, maintained 110 network/systems performance health; equipped global cyber-security operations for 1,200 medical facilities with real-time information
• Established first Splunk MLTK introductory training session, standardized comms protocols traffic analysis, fingerprint & signature analytics; sustained network protection for 15.6 million veterans
Lead Data Scientist | Deloitte & Touché, LLP. (Apr 2021 – Feb 2023)
• Spearheaded DHS/CBP Queuing modeling, optimized assets’ allocations across entire CONUS national borders; sustained U.S. Border Patrol Strategy and safety of ~19,000 security agents.
• Led social network analysis, and MisDis Information advanced analytics including authentication, attribution, and behavioral analytics, liaised information with cross-functional teams in support of Government & Public Service practice
• Steered public health K-means/Clustering analysis, identified groups at risk; drove vaccination campaigns priorities for ~ 800,000 regional population
Data Scientist Intern | Accenture Federal Services (Oct 2020 – Jan 2021)
• Internship with Accenture Federal Services; led social media/web content scraping, topic modeling, sentiment analysis, and exploratory data analysis tradecraft to uncover hidden data; answered 27 RFIs
Senior Data Analyst, Intelligence Operations | United States Air Force (May 2014 – Mar 2021)
• Managed intelligence collection, analysis, and reporting functions. Directed training and allocation of over 2,500 Intelligence Analysts. Sustained intelligence operations in support of the IC and global security.
EDUCATION
Master of Science in Data Analytics (MSDA) | University of Maryland, Global Campus
• Integrated Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) heuristic algorithms to enhance Federal Aviation Administration’s NextGen R&D Office aircraft’s lateral deviation anomaly detection tools.
• Designed Conditional Inference Tree (CTREE) for classification and interpretation of CTGs, optimizing identification of at-risk newborns and their mothers.
• Developed an irregular-cells Convolutional Neural Network (CNN) predictive model for early detection of breast carcinoma.
• Classified Landsat Multi-spectral Scanner images using K-means model, base-lining image study with vector/centroid pixel- dimension features.
• Designed Conditional Inference Tree (CTREE) for classification and interpretation of CTGs, optimizing identification of at-risk newborns and their mothers.
• Developed an irregular-cells Convolutional Neural Network (CNN) predictive model for early detection of breast carcinoma.
• Classified Landsat Multi-spectral Scanner images using K-means model, base-lining image study with vector/centroid pixel- dimension features.
Bachelor of Science in Information Technology Management | American Military University
• Applied industry driven techniques throughout complete IT project’s development lifecycle
• Applied principles and practices of business solutions, database systems, networks, information systems, information security, and information technology project planning
• Applied principles and practices of business solutions, database systems, networks, information systems, information security, and information technology project planning
TECHNICAL COMPETENCIES
• Programming: Python, R, SQL, C#, MATLAB, SAS, VSC, Git, TensorFlow, Keras, PyTorch
• Data Science Tools: Scikit-learn, Pandas, Numpy, Seaborn, Matplotlib, Plotly, Tidyverse
• Cloud & BI: Azure, AWS, GCP, KNIME, Qlik, Tableau, Power BI, PowerApps, IBM Cognos Analytics, SAS E-Miner
• Machine Learning: Time series forecasting, econometric models, classification and optimization techniques
• Development: Shiny, Quarto, Rmarkdown, Dash, Boken, Streamlit, Flask
• Data Science Tools: Scikit-learn, Pandas, Numpy, Seaborn, Matplotlib, Plotly, Tidyverse
• Cloud & BI: Azure, AWS, GCP, KNIME, Qlik, Tableau, Power BI, PowerApps, IBM Cognos Analytics, SAS E-Miner
• Machine Learning: Time series forecasting, econometric models, classification and optimization techniques
• Development: Shiny, Quarto, Rmarkdown, Dash, Boken, Streamlit, Flask