Data Scientist

Posted 2 Days Ago
Camp Springs, MD, USA
In-Office
135K-145K
Mid level
Information Technology • Professional Services • Consulting • Defense
The Role
Perform advanced analytics and predictive modeling to optimize USCIS field operations. Build dashboards, forecast workloads, track KPIs, conduct impact analyses, run deterministic and probabilistic models, support testing cycles, and advise on IT/AI enhancements to improve staffing and operational efficiency.
Summary Generated by Built In

Description

Location: Camp Springs, MD & Authorized Telework (Hybrid)

Position Summary:

This role provides advanced data analytics, predictive modeling, and business intelligence support to USCIS Field Operations. The Data Scientist analyzes complex immigration operational data to support data-driven decision making, staffing optimization, and performance improvement.

Responsibilities:

  • Develop and implement data-driven strategies to optimize operational efficiency, with quarterly progress reports on KPIs
  • Conduct technology assessments and provide actionable recommendations for IT enhancements, including adoption of emerging technologies such as AI
  • Establish performance monitoring mechanisms to track project outcomes focused on USCIS objectives, providing monthly status reports
  • Provide predictive modeling and workload forecasting of key immigration and demand metrics, measuring accuracy and impact on decision-making
  • Provide analytical knowledge and techniques regarding business process, workload/staffing modeling, and exploration and predictive analytics, including the Staffing Allocation Model (SAM) tools to assess efficiency gains and staffing changes
  • Develop and track KPIs, providing data-driven recommendations for continuous improvement. Develop implementable project metrics with data driven collection plans to project ROI of proposed initiatives, determine source data and baseline current state, and quantify impact post implementation
  • Use collected customer experience data to develop systems, programs, and process improvements to customer and user experiences
  • Build interactive dashboards with real-time performance data to enhance transparency and decision-making using Tableau, Power BI, Python and Databricks
  • Expand on summary statistics using Tableau to run new and existing deterministic and probabilistic models addressing eligibility, risk, and complexity screening protocols. Interpret complex immigration data impacting SAVE and E-Verify programs.
  • Incorporate advanced statistical techniques (i.e., machine learning and hierarchical regression), where appropriate to use a statistical model to infer future results
  • Conduct trend analysis and impact assessments of operational immigration data to optimize operational efficiency.
  • Hold meetings and workshops with SMEs to understand data collection and analyses
  • Develop structured readiness plans with clear objectives, timelines, and success metrics
  • Coordinate alpha/beta testing cycles with documented feedback loops, ensuring effective issue resolution
  • Support reporting of project/product implementation by working with PMs/POs to provide recurring reporting. Provide detailed post-deployment reports, including performance metrics, lessons learned, and improvement recommendations.
  • Support risk management, post-deployment evaluations, and continuous improvement initiatives

Requirements

Required Qualifications:

  • Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field 
  •  3–10 years of relevant experience applying statistical and machine learning techniques to operational data, preferably in a federal environment 
  • Predictive modeling and workload forecasting of key immigration and demand metrics
  • Staffing Allocation Model (SAM) tools; workload and staffing modeling
  • Development of interactive dashboards using Tableau, Power BI, Python, and Databricks
  • Advanced statistical techniques including machine learning and hierarchical regression
  • Expanding Tableau-based deterministic and probabilistic models addressing eligibility, risk, and complexity screening protocols
  • Interpretation of complex immigration data, specifically data impacting SAVE and E-Verify programs
  • Building and tracking KPIs with data-driven collection plans to project ROI of proposed initiatives
  • Trend analysis and impact assessments on operational immigration data
  • Conducting workshops with SMEs to understand data collection and analysis needs

Physical Demands: The physical demands and work environment characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable people with disabilities to perform the described essential functions of the job.

  • Physical demands: While performing the duties of job, employee is required to stand; walk; sit; use hands to fingers, handle or feel objects; reach with hands and arms; talk and hear; type/use computer and phone. Prolonged Sedentary work that primarily involves sitting/standing. Light work that includes moving objects up to 40 pounds.
  • Non-Physical demands: Frequently requires performing multiple tasks simultaneously, working closely with others as part of a team, and tedious or exacting work. Occasionally requires time pressures, emergency situations, and frequent change of tasks. Rarely requires irregular schedule/overtime and noisy/distracting environment.
  • Work environment: Generally, an office-type position. The noise level in the work environment is usually quiet in office settings and moderate in other situations. This is primarily a work-from-home position, with some travel to Corporate Office area as needed. Requires eligibility to work in the US and may require a background investigation or security clearance.

Please note, this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice. To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform essential job functions. Email [email protected] if you would like to request an accommodation.

Skills Required

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field
  • 3-10 years relevant experience applying statistical and machine learning techniques to operational data, preferably in a federal environment
  • Predictive modeling and workload forecasting of key immigration and demand metrics
  • Experience with Staffing Allocation Model (SAM) tools and workload/staffing modeling
  • Development of interactive dashboards using Tableau, Power BI, Python, and Databricks
  • Advanced statistical techniques including machine learning and hierarchical regression
  • Expand Tableau-based deterministic and probabilistic models addressing eligibility, risk, and complexity screening protocols
  • Interpretation of complex immigration data, specifically data impacting SAVE and E-Verify programs
  • Building and tracking KPIs with data-driven collection plans to project ROI
  • Trend analysis and impact assessments on operational immigration data
  • Conducting workshops with subject matter experts to understand data collection and analysis needs
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The Company
23 Employees
Year Founded: 2007

What We Do

QED Enterprises, Inc. is a Service-Disabled Veteran-Owned small business (founded 2007) headquartered in Stafford, VA, that provides technology and professional services to U.S. federal agencies and the Department of Defense. QED delivers IT services, program/project management, financial management, strategic planning, and facilities information management via multiple government acquisition vehicles, focusing on mission-driven solutions for public-sector clients.

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