Data Scientist

Created at: January 15, 2026 00:12

Company: Food Safety and Inspection Service

Location: Raleigh, NC, 27561

Job Description:

This position is located within the Office of Planning, Analysis, and Risk Management (OPARM). OPARM is the FSIS centralized analytics group and tasked with integrating and analyzing relational data. The program also provides data visualization and analytics services to support FSIS decision-making, policy development, risk management, and strategic planning.
Applicants must meet all qualifications and eligibility requirements by the closing date of the announcement including specialized experience and education, as defined below. For the GS-13 grade level: Applicants must have one year of specialized experience (equivalent to the GS-12 grade level) that demonstrates: Using Python or R to extract, manipulate, and integrate information from relational databases. Creating interactive reports or dashboards using programming languages and frameworks (e.g., Python, R, Qlik, or similar) Leading technical initiatives, including planning, coding, testing, and deploying solutions that support organizational data and reporting needs. Developing oral and written presentations communicating complex and technical analyses to inform, influence, and persuade a variety of audiences. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social). Volunteer work helps build critical competencies and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.
Perform data cleaning and visualization.
Perform trend analysis and algorithm development.
Develop new prescriptive analytics used in decision making.
Present alternate solutions to analytics and future concepts.
Develop statistical models and machine learning models.
Analyze outputs from analyses.
Perform quality checks on model and analysis output.
Develop recommendations for data integration.
Develop testing hypothesis.


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