OPERATIONS RESEARCH ANALYST
Immediate Office of the Chief of Naval Operations
Summary You will serve as a OPERATIONS RESEARCH ANALYST in the DATA ANALYTICS DIRECTORATE of NAVSAFECOM. Responsibilities You will coordinate the development and management of data science and artificial intelligence/machine learning projects, including objectives, project plans, schedules, and support requirements. You will translate naval safety questions and operational needs into analytical studies, determine data collection requirements, select and adapt methodologies, organize project phases, and derive conclusions and recommendations. You will design and implement relational or dimensional data models and repeatable data pipelines to extract, integrate, clean, transform, and validate data for analysis. You will develop, test, and document reusable analytical code using tools such as Python and SQL in environments such as Databricks. You will evaluate and coordinate requests for data science and machine learning analysis, advise stakeholders on feasibility, and adapt analytical approaches or propose alternative data sources to address data limitations and time constraints. You will develop reports of analytical findings and model conclusions, including charts, tables, dashboards, and presentations. You will provide recommendations that help technical and nontechnical audiences, including senior leaders, make informed safety and risk decisions You will initiate and conduct complex research on safety-related topics, including those with limited precedent, and develop, train, and validate machine learning models for prediction, classification, and risk analysis. You will use statistical analysis and appropriate evaluation methods to assess model performance, assumptions, uncertainty, and limitations. Requirements Conditions of Employment Qualifications In addition to the Basic Requirements for this position, your resume must also demonstrate at least one year of specialized experience equivalent to the next lower grade level (GS-12) or pay band in the federal service or equivalent experience in the private or public sector as a professional Operations Research Analyst performing the following duties: 1. Advanced Modeling - Experience independently developing, validating, and applying machine learning models for prediction, anomaly detection, or risk analysis, including evaluating model performance, assumptions, and limitations. 2. Programming & Pipelines - Professional experience performing hands-on data engineering and exploratory data analysis using languages such as Python and SQL including building ETL/data pipelines to ingest, integrate, clean, validate, and transform data for analysis and machine learning. 3. Experience leading or substantially contributing to data science project lifecycles, including defining analytical objectives, identifying data requirements, coordinating data integration, addressing data quality, and documenting analytical methods, model validation results, and recommendations. 4. Experience designing interactive dashboards (e.g., Qlik, Tableau, PowerBI) and presenting highly technical model outputs, limitations, and predictive insights to Flag-level leadership. Additional qualification information can be found from the following Office of Personnel Management website: Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., professional, philanthropic, religious, 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. Education Applicants must meet the following positive education qualifications requirements of the Office of Personnel Management (OPM) Qualifications Standards Manual: Applicants must possess: Degree: in operations research; or 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. Additional Information This position is covered by the Department of Defense Priority Placement Program. Additional vacancies may be filled by this announcement. A tentative offer of employment will be rescinded if the selectee fails to meet the pre-employment requirements, including failure to report to any of the scheduled appointments. During the application process you will have the ability to opt-in to make your resume available to hiring managers in the agency who have similar positions in the local commuting area. Depending on the hiring organization and the position being filled, job requirements (e.g., security clearance, travel, drug testing, financial disclosure filing, bargaining unit status, etc.) may vary. Other hiring managers filling similar positions may offer relocation expense reimbursement and/or may offer recruitment incentives for new employees, depending on funding availability and in accordance with policy. If you opt-in and are referred on a certificate, your resume will be available to other hiring managers for 180-days from the date the job announcement closes. Opting in does not impact your application for this announcement, nor does it guarantee further consideration for additional positions. Federal annuitant information: The selection of an annuitant is subject to the Department of Defense and Department of the Navy policy on the employment of annuitants. Policy information may be found at: PPP applicants will be placed at the FPL, if determined Well Qualified (WQ). To receive priority consideration, the FPL must be the same grade level or equivalent of the retained grade or the grade held immediately prior to separation. Military Spouse Preference applicants will be placed at the highest grade for which they have applied and are determined Best Qualified (BQ). A BQ military spouse possesses knowledge, skills, abilities, and competencies comparable to others who meet the competitive referral criteria for the specific position.
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