Summary
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Duties
The United States Space Force (USSF) at Randolph AFB, San Antonio, Texas is searching for a Senior Data Engineer, HQSF ETM/TMS (NH-1560-04, GS 14/15 equivalent). Description: The Enterprise Talent Management Office (ETM) seeks a senior Data Scientist/Data Engineer to build and sustain the data capabilities that inform Guardian talent management and senior leader decisions. In this role, you will develop and improve data models, pipelines, interfaces, and infrastructure; integrate diverse data sources; and deliver timely, reliable analytics for human capital policy, workforce planning, and talent operations. You will apply advanced data engineering, statistical analysis, artificial intelligence, machine learning, simulation, and decision-analysis methods to solve complex enterprise challenges. As a technical subject matter expert, you will translate stakeholder needs into technical requirements and turn complex data into clear, actionable recommendations for Space Force decision-makers. You will lead data engineering and analytics initiatives; develop scalable data pipelines, models, dashboards, and interfaces; strengthen data quality, governance, and reliability; and prepare concise reports and briefings for senior, nontechnical audiences. If you have strong experience in programming, data architecture, statistical and predictive modeling, and leading technical projects, join ETM to help deliver a more data-driven approach to Guardian talent management. The ideal candidate has a strong background in data science, statistics, mathematics, computer science, or a closely related discipline and has demonstrated success applying rigorous quantitative methods to complex organizational or mission problems. Background and Experience: - Developing and maintaining data pipelines, data models, databases, and data infrastructure. - Using SQL and scripting or statistical-computing languages, such as Python or R, for data processing and analysis. - Designing, training, validating, and evaluating artificial intelligence or machine-learning models. - Performing statistical analysis, predictive modeling, simulation, optimization, or decision analysis. - Establishing data governance, metadata, data-quality, testing, and monitoring practices. - Leading technical projects or teams; managing competing priorities; and delivering results on schedule. - Explaining complex technical findings through concise reports and briefings for senior, nontechnical audiences. - Applying analytics to human capital, workforce planning, personnel, organizational performance, or related mission areas. Education and Training: - Mandatory Degree Requirement: A bachelor's degree in mathematics, statistics, computer science, data science, or another field directly related to the position; or a qualifying combination of education and experience consistent with the applicable position qualification standard. At least 24 semester hours in a combination of operations research, mathematics, probability, statistics, mathematical logic, science, or subject-matter courses requiring substantial competence in college-level mathematics or statistics. At least 3 of the 24 semester hours must have been in calculus. Key Skills and Abilities: Knowledge of computer science, data analytics, statistics, and mathematics. Knowledge of data modeling, database design and data storage concepts. Knowledge of data governance, metadata management and regulatory considerations for data use. Data engineering skills with demonstrated ability to lead teams in a senior or project lead role. Ability to design and deliver scalable data pipelines and data models that reflect reproducible and repeatable engineering processes. Programming skills and proficiency in data query languages and scripting for data processing. Skill in programming, training, and validating AI and ML models to synthesize disparate and messy data to meet mission requirements. Skill in implementing data quality, testing and monitoring practices for data production systems.
How you will be evaluated
Knowledge, Skills and Abilities (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies as related to the series and grade of the position being filled. Final qualifications determinations will be assessed based on OPM's General Schedule Qualifications Standards found here: Interviews: You will be contacted by e-mail and/or telephone if your application is identified as qualifying for a position being filled. An interview may be conducted. If interviewed, you will be asked to address the same knowledge, skills, abilities and/or competencies used to initially qualify your application for the position.