Senior Data Scientist

Unissant•Washington, VA

5d•Onsite

About The Position

Unissant, Inc. is seeking a Senior Data Scientist to join their team in Washington, DC, in support of the Department of Homeland Security (DHS), Immigration and Customs Enforcement (ICE), Law Enforcement Systems and Analysis (LESA) program within the Strategy and Operations Analysis (SOA) Unit. The SOA Unit provides advanced analytics, visualization, and modeling capabilities spanning the entire Enforcement Lifecycle to inform ERO and ICE strategic and budgetary decision-making. SOA utilizes predictive analytics, simulation, and optimization modeling to forecast resource needs, support congressional responses, and drive organizational planning at headquarters and field levels. The ideal candidate is a recognized data science leader with deep expertise in advanced ML, MLOps, operations research, and data architecture, and the ability to serve as the senior analytical voice for the SOA Unit.

Requirements

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.
Bachelor's Degree required.
Excellent verbal and written skills; experienced presenting complex analytical findings to senior federal leadership and non-technical audiences.
Ability to produce reports and briefings consistent with FOUO/LES confidentiality standards.
Active ICE clearance required; preference for candidates currently cleared or cleared within the last two years.
Ability to obtain and maintain required clearance level is a condition of employment.

Nice To Haves

Preferred fields for Bachelor's Degree: 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.
Advanced ML/AI certifications (AWS ML Specialty, Google Professional ML Engineer, Azure AI Engineer) strongly preferred.
MLOps, Databricks, or HPC certifications are a plus.

Responsibilities

Serve as the senior technical lead for the SOA analytical program: architecting, developing, and operationalizing advanced machine learning solutions including deep learning (CNNs, RNNs, Transformers), ensemble methods, and AI-driven decision-making tools for resource allocation and prioritization problems.
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.