BASIC REQUIRED SKILLS:

• Strong knowledge and demonstrated application of SQL (Structured Query Language), Microsoft Excel, and R or Python (statistical programming).
• Experience in data visualization and interactive dashboard development, machine learning concepts and tools, working independently and collaboratively in support of technical tasks, and presentation development and delivery.
• Ability to work with large datasets and draw meaningful insights from complex variables.
• Experience supporting moderately complex projects and producing high-quality technical documentation.

OTHER DESIRED SKILLS:

• Familiarity with cloud-based analytics environments, particularly Databricks
• Experience using Git for version control and collaborative development
• Background in regulated environments, particularly FDA or other HHS agencies
• Understanding of data quality and metadata management in a public health surveillance context
• Ability to serve as a database administrator as collateral duty

EDUCATION:

• Bachelor’s degree in Mathematics, Economics, Computer Science, Information Management, or Statistics
  Minimum of five (5) years of experience in the field or in a related area
  Job Type: Full-time
  Pay: $90,000.00 - $100,000.00 per year
  Work Location: In perso

• Perform data loading, extraction, transformation, and loading (ETL) processes for FDA datasets.
• Prepare data reports and analyze trends, links, patterns, and anomalies in structured and unstructured data.
• Develop and deliver interactive dashboards and data visualizations to communicate surveillance model output (e.g., SSM) using tools such as Qlik and Posit.
• Prepare data presentations and visual narratives for FDA stakeholders, ensuring insights are clearly communicated.
• Contribute to the development, maintenance, and documentation of data pipelines supporting surveillance and quality analytics programs.
• Collaborate with subject matter experts and cross-functional teams to understand data needs and provide technical recommendations.
• Investigate relationships between variables to identify trends, root causes, and potential quality issues.
• Document unmet data needs of stakeholders and communicate data quality or source issues.
• Clean, organize, and perform analysis on large and heterogeneous datasets.
• Attend and participate in weekly progress meetings and submit weekly status updates and monthly summary reports.
• Track all validation activities and project progress using Excel and submit weekly reports via email.
• Complete all mandatory trainings by required deadlines and maintain training records.
• Ensure deliverables meet documentation, security, and accessibility standards.