Data Scientist

Unissant•Washington, DC

3d•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 Statistical Tracking Unit (STU). The STU is responsible for ensuring accountability, consistency, and efficiency in the statistical reporting of ICE operations. STU supports analysis of key performance metrics, provides ad hoc analysis and reporting for congressional inquiries, interagency requests, litigation, and FOIA, and assesses and improves reporting tools including the ICE Integrated Decision Support System (IIDS) and ENFORCE. The ideal candidate is a data scientist with strong predictive modeling, feature engineering, and model evaluation skills, with particular ability to support official reporting workflows, data quality monitoring, and business requirements development in a high-accountability government environment.

Requirements

5+ years of experience in data science, applied machine learning, statistical analysis, or quantitative reporting, preferably in a federal law enforcement, compliance, or statistical reporting environment.
Demonstrated experience in predictive modeling and ML techniques: supervised learning (classification, regression), unsupervised learning (clustering), and ensemble methods.
Strong feature engineering skills across structured, categorical, and time-series data common to government enforcement and immigration datasets.
Experience designing and implementing model/report validation frameworks and population audits; familiarity with ICE systems (ENFORCE, IIDS, OBIEE/OAS) is a strong plus.
Ability to work in a high-accountability reporting environment, meeting strict delivery deadlines with accurate, error-free deliverables consistent with STU SOPs.
Experience supporting FOIA, litigation, or congressional reporting requests preferred.
Strong SQL skills for querying government databases; Python and/or R programming; experience with Databricks, Oracle OBIEE/OAS, or UiPath is a plus.
Proficiency with data visualization tools: Python (matplotlib, seaborn, Plotly), Tableau, Qlik, Power BI, GIS/ArcGIS.
Bachelor's Degree required. Preferred fields: Computer Science, Data Science, Statistics, Mathematics, or related discipline.
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

Master's Degree in a quantitative discipline preferred.
Data science or ML certifications (e.g., AWS Certified Machine Learning, Databricks ML Associate, or equivalent) preferred.
Tableau, QLIK, or SQL certifications are a plus.

Responsibilities

Develop and implement predictive modeling and machine learning solutions to support STU statistical reporting, data quality monitoring, and enforcement analysis within the immigration lifecycle.
Perform feature engineering: identifying, constructing, and selecting relevant variables from structured and unstructured data in ICE systems of record (ENFORCE, IIDS, and related databases) to optimize model and report performance.
Design and execute comprehensive model evaluation and validation frameworks including cross-validation, A/B testing, precision/recall analysis, and population/filter validation per STU standard operating procedures.
Provide data quality monitoring: analyze data to identify patterns, data quality issues, and anomalies; document findings and provide recommendations to federal staff in writing.
Complete a "Weekly Population Report Validation" process: validate all standard populations and filters in systems of record by the first business day of each week; communicate data quality issues to federal staff by 3:00 PM EST on the first business day of each week.
Gather business requirements, design, and execute recurring and ad-hoc reports from databases of record at prescribed frequencies for federal staff review; conduct peer reviews of deliverables daily or as requested.
Gather business requirements and draft reporting methodologies; participate in the testing and validation of business rule implementations; provide final training documentation as directed by the STU Unit Chief.
Identify data resources, research historical data, integrate structured and unstructured data from disparate sources, and incorporate new data from systems as required.
Support EOFY (End of Fiscal Year) Management: conduct population audits, validate fiscal year reports, identify data quality issues, and draft updated methodologies for new fiscal year reporting.
Co-lead STU working groups (including the STU Database Working Group); identify gaps for LESA business tool development; draft technical requirements for ITM; provide UAT and validation of implementations.
Evaluate and provide recommendations for current and emerging business tools: SQL, AI, Tableau, GIS, Python, QLIK, Databricks; support FOIA and litigation data pulls from ERO systems.
Create data visualizations and storytelling artifacts using standard and non-standard datasets; present data in organized formats for STU reporting and congressional/interagency deliverables.