Data Scientist

Unissant•Washington, VA

5d•Onsite

About The Position

Unissant, Inc. is seeking a 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 planning, analysis, and technical support spanning the entire Enforcement Lifecycle, delivering advanced analytics, visualization, and modeling capabilities to inform ERO and ICE management decisions at headquarters and field levels. SOA utilizes advanced predictive analytics, simulation, and modeling to forecast implications of resource needs, policy shifts, and migration changes. The ideal candidate is an analytically rigorous data scientist with experience applying machine learning and statistical modeling to complex law enforcement and operational datasets.

Requirements

3+ years of experience in data science, machine learning, advanced analytics, or related analytical disciplines, preferably supporting federal law enforcement, DHS/ICE/ERO, or national security missions.
Demonstrated experience developing and applying predictive modeling and machine learning techniques, including regression, classification, clustering, time series, and ensemble methods.
Hands-on data wrangling and ETL experience using Python, R, and/or SQL; familiarity with federal government categorical datasets and data warehouses.
Proficiency applying statistical methods including multiple correspondence analysis (MCA), principal component analysis (PCA), and association rule mining.
Experience building dashboards, visualizations, and geospatial analytical products using tools such as Tableau, Qlik, Power BI, ArcGIS, matplotlib, or seaborn.
Familiarity with machine learning and AI libraries such as TensorFlow, PyTorch, Keras, h2o, mlr, mpi4py, or scikit-learn.
Experience working in secure government data environments and preparing executive-level analytical reports using tools such as RMarkdown or Jupyter Notebook.
Bachelor's Degree required.
Excellent verbal and written skills; able to present technical findings and performance data to non-technical audiences including federal leadership.
Ability to write clear, concise reports and briefings consistent with FOUO/LES handling requirements.
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

Experience with Discrete Event Simulation (DES) modeling or operations research methods is a strong plus.
Master's Degree or PhD in a quantitative field preferred.
Data science or machine learning certifications such as AWS Certified Machine Learning, Google Professional ML Engineer, or Databricks ML Associate preferred.
Tableau, Qlik, or ArcGIS certifications are a plus.

Responsibilities

Develop, maintain, and enhance predictive models and machine learning solutions, including supervised and unsupervised methods, to support ICE/ERO mission analytics, resource forecasting, and operational decision-making within the SOA Unit.
Contribute to the development and maintenance of LESA's suite of Discrete Event Simulation (DES) models to capture components of the Immigration Enforcement and Removal Lifecycle.
Perform data wrangling and ETL operations to acquire, clean, integrate, and transform complex datasets from flat files, data warehouses, and external/academic sources into formats suitable for modeling and analysis.
Design and develop data visualizations, dashboards, and analytical products using standard and non-standard datasets to identify patterns, insights, and geospatial trends in support of SOA reporting.
Maintain and improve LESA-related geospatial capabilities and Logistics Optimization Decision Support Tools.
Assess and apply current and emerging AI, visualization, modeling, and business intelligence technologies, including Python, GitHub, Qlik, Tableau, ArcGIS, Databricks, and Palantir Foundry.
Streamline reporting on key performance indicators across the data and visualization enterprise; promote information sharing among field and HQ stakeholders.
Support DHS model accreditation processes, including drafting model documentation covering design methodology, requirements, decision-making applications, and stakeholder engagement.
Support ad-hoc activities, model and tool enhancements, and special projects including congressional inquiries, policy change analysis, and ERO strategic logistics initiatives.
Integrate structured and unstructured data from disparate sources; implement data cleaning, validation, and quality review processes; implement security measures for sensitive law enforcement data.