You must meet the Basic Requirements and the Minimum Qualifications to qualify for the Data Scientist, GS-1560-13/14, as described below. Basic Requirements: Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position. OR A combination of education and experience: Courses equivalent to a major field of study (30 semester hours) in mathematics, statistics, computer science, data science or field directly related to the position, plus additional education or appropriate experience. Minimum Qualifications For GS-13: Applicants must have 52 weeks of specialized experience equivalent to at least the next lower grade level, GS-12 in the Federal Service. Specialized Experience is the experience that equipped the applicant with the particular knowledge, skills, and abilities (KSA's) to perform the duties of the position successfully, and that is typically in or related to the position to be filled. To be creditable, specialized experience must have been equivalent to at least the next lower grade level. Qualifying specialized experience for GS-13 includes: 1. Utilizing statistical or mathematical software to generate descriptive statistics, developing statistical models and graphics, tracking and assessing data. 2. Development of predictive and statistical models using SQL, R, SAS, Python, Spark, Jupiter, notebook-based workflows, or other data analytics tools. 3. Applying scientific methods, processes, algorithms, and systems to extract knowledge, produce findings and insights, and apply across a broad application of domains. For GS-14: Applicants must have 52 weeks of specialized experience equivalent to at least the next lower grade level, GS-13 in the Federal Service. Qualifying specialized experience for GS-14 includes: 1. Applying scientific methods, processes, algorithms, and systems to extract knowledge, produce findings and insights, and apply across a broad application of domains. 2. Utilizing statistical or mathematical software to generate descriptive statistics, developing statistical models and graphics, tracking and assessing data. 3. Development of predictive and statistical models using SQL, R, SAS, Python, Spark, Jupiter, notebook-based workflows, or other data analytics tools. 4. Analyzing and interpreting data across multiple operational domains, including workers' compensation claims and program integrity review, cost accounting and financial performance analysis, and end_to_end revenue cycle management. Experience in Medical, Pharmaceutical, and/or Healthcare environments is preferred but not required.