Data Scientist

About the role

This role requires paramount knowledge based on academic and experiential learning in the area of discipline of Data Science. The Data Scientist serves as a non-supervisory, technical expert in LGY's Business Insight and Data Solutions (BIDS) group ensuring authoritative data is prepared and available to stakeholders in support of data-informed decision making. To qualify for this position, applicants must meet all requirements by the closing date of this announcement:06/16/2026. Individual Occupational Requirement: This position does have an IOR (Individual Occupational Requirement) that must be met in addition to the basic Specialized Experience qualifications. In order to qualify for this position, you must have the education or experience listed below: Education: 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 Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience. AND TIME-IN-GRADE REQUIREMENT: Applicants who are current Federal employees and have held a GS grade any time in the past 52 weeks must also meet time-in-grade requirements (unless if in the commuting area and eligible for a non-competitive hiring authority such as Schedule A, VRA, or 30% or more disabled Veterans). For a GS-14 position you must have served 52 weeks at the GS-13 level. The grade may have been in any occupation, but must have been held in the Federal service. An SF-50 that shows your time-in-grade eligibility must be submitted with your application materials. These requirements also apply to former Federal employees applying for reinstatement and those applying for a Veterans Employment Opportunities Act of 1998 (VEOA) appointment. MINIMUM QUALIFICATION REQUIREMENT: You may qualify based on your experience and/or education as described below: GS-14 Level: Specialized Experience: One year of specialized experience (equivalent to the GS-13 grade level in the federal service); experience that equipped the applicant with the particular knowledge, skills and abilities (KSA's) and other characteristics to perform successfully the duties of the position, and that is typically in or related to the work of the position to be filled, in the normal line of progression for the occupation in the organization. Specialized experience is defined as: Experience in applying a wide range of concepts, approaches, practices, regulations, policies, precedents, and analytical, and procedures related to data science. Experience planning and executing a variety of data science and/or analytics projects. Experience applying programming logic, data management, data governance, and data optimization strategies. Experience applying coding, data, and data processing expertise to solve business problems. Assists in developing new or improved business processes or methodologies for assigned programs and projects. There is no education substitution for this grade level. Volunteer Experience: 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; religions; spiritual; community; student; social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience. Full vs. Part-Time Employment: Full-time employment is considered to be at least 35 hours per week. Part-time experience will be credited on a pro-rated basis; when including part-time employment in your resume you must specify the average hours worked per week. Physical Requirements: The work is principally sedentary. For more information on these qualification standards, please visit the United States Office of Personnel Management's website at http://://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/.

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