Data Scientist II

Client First Technologies•Camp Springs, MD

8h•Hybrid

About The Position

Client First Technologies is seeking a Data Scientist II to support a Government customer. This role involves providing advanced analytical support, predictive modeling, and business intelligence capabilities. The Data Scientist II will be responsible for developing and maintaining dashboards, KPI frameworks, and models, interpreting complex data, and applying statistical and machine learning techniques to improve data-informed decision-making and operational efficiency across the customer's programs. This is a full-time position located in Camp Springs, MD, with the possibility of telework. The position is contingent upon contract award.

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field required.
Minimum of five (5) years of experience in data science, data analytics, or a closely related field.
Demonstrated proficiency in Tableau, Power BI, Python, and Databricks, or similar data analysis and visualization platforms.
Experience with predictive modeling, machine learning techniques, and statistical analysis in an applied setting.
Experience with hierarchical regression, probabilistic modeling, and deterministic modeling.
Ability to communicate complex data findings clearly to non-technical stakeholders and senior leadership.
Experience developing KPI frameworks and business intelligence dashboards in support of federal program management.
Must be able to sit and stand for extended periods of time.
This position is subject to a DHS background investigation and must meet eligibility requirements for access to Sensitive But Unclassified (SBU) information.

Nice To Haves

Master's degree in a related field preferred.
Familiarity with DHS immigration systems and data preferred.
Occasional travel and overtime may be required.

Responsibilities

Provide predictive modeling and workload forecasting of key metrics, measuring accuracy and impact on decision-making.
Apply analytical knowledge and techniques in business process analysis, workload and staffing modeling, and predictive analytics, 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 the Return on Investment (ROI) of proposed initiatives.
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 using tools such as Tableau, Power BI, Python, and Databricks to enhance transparency and decision-making.
Expand on summary statistics using Tableau to run new and existing deterministic and probabilistic models addressing eligibility, risk, and complexity screening protocols.
Incorporate advanced statistical techniques, including machine learning and hierarchical regression, where appropriate to infer future results from operational data.
Conduct trend analysis and impact assessments of operational data to optimize efficiency.
Hold meetings and workshops with subject matter experts to understand data collection methodologies and analytical requirements.