Data Scientist - Part Time *Remote*

Type of Requisition:

Pipeline

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

NACI (T1)

Job Family:

Data Science and Data Engineering

Job Qualifications:

Skills:

Code Pipeline, Data Analysis, Data Science

Certifications:

None

Experience:

7 + years of related experience

US Citizenship Required:

No

Job Description:

GDIT is hiring a Data Scientist to provide data management, analytic, and visualization support for our program with HRSA Organ Procurement Transplant Network – Patient Safety. The program’s mission is to support the Organ Procurement and Transplantation Network (OPTN) in safeguarding patient safety and ensuring consistent, effective oversight of member performance and policy compliance across the national transplant system. This mission advances by enabling rigorous monitoring, case review, committee support, and facilitation of compliance standards that uphold regulatory requirements and protect public health. These functions collectively strengthen the integrity, accountability, and reliability of the U.S. organ transplantation system.

Position is for part-time employment with GDIT and will work remote.

Duties include:

• Conduct high-level data interpretation and analysis of medical data using R and PowerBi
• Develop and test innovative data analysis and statistical methods or applications to enhance insight of Patient Safety program performance. 
• Provide technical assistance in data management, analysis, and visualizations to HRSA and field staff.
• Prepare written summaries and presentations that reflect the results of the data analysis and present findings to agency leadership
• Build data dashboards in various platforms including Excel and Business Intelligence platforms
• Support automation of data pipelines
• Liaise with stakeholders across different tasks/departments
• Manage unstructured patient level data and workflows to prepare for meaningful data analysis
• Develop methods, processes, or checks to assess and improve the quality of Patient Safety data across the data life cycle from reporting, entry, access, extraction, and use. 

Qualifications:

Required:

• Education: BA/BS with 7 years of relevant experience OR Master’s degree in Statistics, Data Science, Data Analytics, Health Informatics, or related field of study
• A minimum of 5 years’ experience in data analysis and data science with a background in statistics, another quantitative discipline, or computer science.
• Understanding of data management principles using R, Power Query and/or SQL
• Proficiency in data wrangling (querying/connecting, transposing, merging, filtering, aggregating, cleaning) of large complex datasets using at least one of R, PowerBi, SQL,
• Proficiency in building data models using Power Query or similar
• Ability to create quantitative analytics tools, visualizations and applications in more than one of the following platforms: Excel, PowerBI, MicroStrategy, Tableau, R Studio/R Shiny, Python/Jupiter

• Expert user of Microsoft Excel, Power Query, and PowerPoint
• Experience with Machine Learning methods and AI

Highly Desired:

• Familiarity with health data, public health, or population health.
• Experience in scripting using RStudio for data management and data visualization purposes
• Knowledge of methods in data science, modeling and/or machine learning
• Experience working with or for a US government agency, including State Department
• Experience working with big datasets and/or patient level data
• Capable of creating geospatial analytic products using RStudio or QGIS

Skills and Attributes:

• Superb interpersonal skills and ability to work effectively as a team member
• Strong verbal communication skills; must be comfortable and effective working with diverse audiences including technical staff, international staff, and others.
• Ability to interpret stakeholder concerns and translate them into analytical questions.
• Ability to work independently, including exploring new lines of investigation with minimal supervisory guidance
• Organized, intuitive, efficient and well-documented coding skills
• Excellent analytical and writing skills
• Exceptional attention to detail
• Passionate about making impact in global health
• Effective oral and written communication skills to communicate assignm