Data Scientist with Security Clearance

Job Description

Conceptualize, plan, design, and develop deep learning/AI algorithms for multi-objective optimization focused on ERO resource allocation, logistics, and enforcement prioritization.

Lead MLOps activities including model versioning (MLflow, DVC), performance monitoring, drift detection, CI/CD pipelines, and retraining workflows in production environments.

Prepare models for official DHS accreditation, producing documentation covering model design, methodology, requirements, decision-making use, analysis of alternatives, and stakeholder engagement.

Lead development, maintenance, and governance of LESA's suite of Discrete Event Simulation (DES) models; promote interoperability of products with other LESA DES models to enhance forecasting and decision-making.

Collaborate with data architects and enterprise architects to define scalable data architecture standards supporting analytical and AI/ML workloads; evaluate infrastructure improvements for AI/ML scalability and performance.

Identify gaps for LESA decision support tool development: opportunities to collect new data, improve data quality, and improve forecasting methodologies, reporting, and scenario planning capabilities.

Maintain and improve geospatial capabilities and Logistics Optimization Decision Support Tools; evaluate emerging AI, modeling, and BI platforms (Python, Qlik, Tableau, ArcGIS, Databricks, Palantir Foundry).

Develop executive-level summary reports and briefings of algorithm results using RMarkdown, Jupyter Notebook, MS PowerPoint, and MS Word for ERO/ICE senior leadership.

Rapidly deploy to support special projects: academic research, proof of concepts, congressional inquiry responses, policy change analysis, and ERO strategic logistics initiatives.

Provide technical leadership and mentorship to junior and mid-level data scientists; conduct code reviews, methodology reviews, and knowledge-sharing sessions.

Work Experience and Job Skills:

• 10+ years of experience in data science, machine learning, or applied AI research, with significant experience supporting federal law enforcement, DHS/ICE/ERO, or national security missions.
• Expert proficiency in advanced ML and AI: deep learning (TensorFlow, PyTorch, Keras), ensemble methods (XGBoost, Random Forest), Bayesian methods, and multi-objective optimization algorithms.
• Demonstrated experience implementing: R libraries (h2o, Keras, mlr) and Python libraries (TensorFlow, PyTorch, mpi4py, scikit-learn); experience with MCA, PCA, and association rule mining.
• Demonstrated MLOps experience: model versioning, monitoring, CI/CD for ML, and deployment in High-Performance Computing (HPC) and cloud environments.
• Experience with DES modeling, operations research, and logistics optimization.
• Deep expertise in data architecture collaboration: designing data pipelines, warehouses, and infrastructure to support large-scale ML workloads.
• Proficiency with geospatial tools (ArcGIS, GIS platforms) and BI tools (Qlik, Tableau, Power BI, Databricks, Palantir Foundry).
• Proven technical leadership; ability to produce executive-level deliverables using RMarkdown, Jupyter Notebook, MS Access, MS Excel, MS PowerPoint, and MS Word.

Qualifications

• Bachelor's Degree required. Preferred fields: Computer Science, Data Science, Statistics, Mathematics, Operations Research, or related discipline.
• Master's Degree or PhD in quantitative discipline (Data Science, Machine Learning, Applied Mathematics, Operations Research) strongly preferred.
• Certificates, Licenses and Registrations: Advanced ML/AI certifications (AWS ML Specialty, Google Professional ML Engineer, Azure AI Engineer) strongly preferred.
• MLOps, Databricks, or HPC certifications are a plus.

Skills

• Excellent verbal and written skills;
• Ability to produce reports and briefings consistent with FOUO/LES confidentiality standards.

Clearance Requirements

Active ICE clearance required; preference for candidates currently cleared or cleared within the last two years.

Travel

Minimal travel expected.

Environmental Requirements

Mainly a routine office environment. May be required to lift up to ten (10) pounds. Flexible in working extended hours.