Data Analyst (HR Analytics) (Hiring Event)
What you'd do
Data Analysts combine mission and business analytics knowledge and a consultative approach to prepare reports, briefings, and communicate recommendations to enable stakeholder decision making. Data analysts identify, collect, structure, and evaluate data from various sources to meet analytic needs and prepare data for analysis using a range of data and visualization tools in alignment with data go
Major duties
ADDITIONAL INFORMATION: Data Analyst (HR Analytics) combine HR mission and business analytics knowledge and a consultative approach to prepare reports, briefings, and communicate recommendations to enable stakeholder decision making regarding human capital issues. Data analysts identify, collect, structure, and evaluate data from various sources to meet analytic needs and prepare data for analysis using a range of data and visualization tool in alignment with data governance, standards, and requirements. They work collaboratively with other HR and data professionals and stakeholders to help implement data structures and interfaces that are discoverable, cataloged, and accessible. Data Analysts apply tools and algorithms to identify trends and patterns in HR data to provide actionable insights to address a variety of mission and business problems. Data Analyst apply their skills to directly support HR programs, initiatives, operations, and decision-making.
What you need to qualify
MANDATORY QUALIFICATION CRITERIA: For this particular job, applicants must meet all competencies reflected under the Mandatory Qualification Criteria to include education (if required). Online resumes must demonstrate qualification by providing specific examples and associated results, in response to the announcement's mandatory criteria specified in this vacancy announcement: 1) Experience analyzing and interpreting statistical data to identify innovative solutions (including AI solutions), trends or relationships among variables and factors that could affect the results of research 2) Experience applying mathematical principles or statistical approaches to solve moderately complex problems in scientific or applied fields 3) Experience preparing statistical reports, to include graphics or other visual representations of information 4) Experience exploring and sharing ideas on the development of innovative solutions (including AI solutions) 5) Experience communicating and conveying data, complex information, and analytical conclusions to a variety of audiences and using a variety of visual tools, techniques, and methods EDUCATION REQUIREMENT: A. Education: Bachelor's degree from an accredited college or university in Data Analytics, Business Intelligence, Mathematics, Statistics, Actuarial Science, Computer Science, Engineering, Information Design, Operations Research, Finance, Information Technology, or a related field. -OR- B. Combination of Education and Experience: A minimum of 24 semester (36 quarter) hours of coursework in any area listed in option A, plus experience that requires the application of tools and algorithms to identify trends and patterns in data, or in a related area that demonstrates the ability to successfully perform the duties associated with this work. As a rule, every 30 semester (45 quarter) hours of coursework is equivalent to one year of experience. Candidates should show that their combination of education and experience totals 4 years. DESIRABLE QUALIFICATION CRITERIA: In addition to the mandatory qualifications, experience in the following is desired: 1) Experience implementing AI technologies and methodologies to solve real-world problems and enhance business processes by framing problems, designing solutions, integrating systems, evaluating metrics, and increasing efficiency. 2) Experience with project management, including the development of project plans, schedules, milestones, and resource allocation; monitoring and communicating status updates for deliverables, contractor performance, and project outcomes 3) Experience applying responsible use of AI systems throughout their lifecycle by validating model outcomes, reliability, identifying and mitigating risks and adhering to legal frameworks, regulatory requirements, ethical principles, and organizational values and expectation. 4) Experience supporting human capital programs, projects, or initiatives that may include recruitment, manpower, workforce planning, benefits, compensation, training and education, and talent development
Before you apply
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