Clarification from the agency

U.S. CITIZENS

• At the GS-13 you will perform the below duties:
• You will coordinate the development and management of data science and artificial intelligence/machine learning (AI/ML) projects, including objectives, project plans, schedules, and support requirements.
• You will work with analysts, engineers, commanders, staff representatives, agency executives, customers, and appropriate organizations.
• 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 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.
• 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.
• At the GS-12 level you will perform the below duties:
• You will develop reports on model conclusions including charts, tables, dashboards, and presentations.
• You will be responsible for receiving, coordinating, and modifying requests for modeling simulation to conform to available data.
• At the GS-11 level you will perform the below duties:
• You will work under senior analyst's indirect supervision in project development and management, justification, plans, schedules, study plan development and support requirements.
• You will evaluate knowledge to identify meaningful knowledge.

Conditions of employment

• Must be a US Citizen.
• Must be determined suitable for federal employment.
• Must participate in the direct deposit pay program.
• New employees to the Department of the Navy will be required to successfully pass the E-Verify employment verification check. To learn more about E-Verify, including your rights and responsibilities, visit e-verify.gov
• Within the Department of Defense (DoD), the appointment of retired military members within 180 days immediately following retirement date to a civilian position is subject to the provisions of 5 United States Code 3326.
• Males born after 12-31-59 must be registered for Selective Service.
• You will be required to obtain and maintain an interim and/or final security clearance prior to entrance on duty. Failure to obtain and maintain the required level of clearance may result in the withdrawal of a job offer or removal.

Qualifications

GS 13: In addition to the basic requirement your resume must also demonstrate at least one year of specialized experience at or equivalent to the GS-12 grade level or pay band in the Federal service or equivalent experience in the private or public sector. Specialized experience must demonstrate the following: 1) Coordinating the development and management of data science or artificial intelligence/machine learning (AI/ML) projects, including project justification, objectives, project plans, schedules, and support requirements with analysts, engineers, commanders, staff representatives, agency executives, customers, and appropriate organizations; (2) Planning and conducting data science projects, including translating operational questions into analytical problems, selecting appropriate methods, organizing project phases, identifying data requirements, collecting and analyzing data, and developing conclusions and recommendations; (3) Implementing relational or dimensional data models and repeatable data pipelines to extract, integrate, clean, transform, and validate data, using documented and tested analytical code and tools or environments such as Python, SQL, Databricks, Apache Spark/PySpark, or comparable technologies; (4) Developing, adapting, and evaluating machine learning methods and models for complex research involving safety, risk, or comparable operational problems, including problems with limited precedent. Relevant activities may include feature engineering, model training, hyperparameter tuning, model validation, and comparison of model performance, assumptions, and limitations using appropriate statistical and evaluation methods; (5) Evaluating and coordinating requests for AI/ML analysis, advising stakeholders on feasibility, and adjusting analytical approaches, data requirements, model inputs, or project scope to address available data, methodological limitations, and time constraints; (6) Developing reports, charts, tables, dashboards, and presentations that explain analytical methods and model results, and communicating defensible conclusions, recommendations, assumptions, and limitations to technical and nontechnical audiences, including senior leaders.

GS-12: In addition to the basic requirement your resume must also demonstrate at least one year of specialized experience at or equivalent to the GS-11 grade level or pay band in the Federal service or equivalent experience in the private or public sector. Specialized experience must demonstrate the following: 1) AI/ML Advanced Modeling- Assisting with designing and deploying machine learning models, simulation-based forecasts, or risk models to identify trends, anomaly patterns, or high-risk areas within operational systems; 2) Programming & Pipelines- performing hands-on data wrangling, building ETL/data pipelines, and conducting exploratory analysis using programming languages such as Python, R, and SQL in environments such as Databricks; 3) Experience in being a part of data science life-cycles, including defining analytical objectives, coordinating cross-agency data integration, managing data governance, and authoring formal model validation reports; 4) Experience designing interactive dashboards (e.g., Qlik, Tableau, PowerBI) and presenting highly technical model outputs, limitations and predictive insights to Flag-level leadership.

GS-11: In addition to the basic requirement your resume must also demonstrate at least one year of specialized experience at or equivalent to the GS-09 grade level or pay band in the Federal service or equivalent experience in the private or public sector. Specialized experience must demonstrate the following: 1) AI/ML Advanced Modeling- Assisting with designing and deploying machine learning models, simulation-based forecasts, or risk models to identify trends, anomaly patterns or high-risk areas within operation systems; 2) Programming & Pipelines- aiding with hands-on data wrangling, building ETL/data pipelines; and conducting exploratory analysis using various programming techniques; 3) Participating in data science life-cycles, including assisting with defining analytical objectives, aiding with cross-agency data integrations and managing data governance; 4) Following prescribed procedures to design interactive dashboards, (e.g., Qlik, Tableau, PowerBI) and participating in presentations.

Additional qualification information can be found from the following Office of Personnel Management website: https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/1500/operations-research-series-1515/

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.

IDEAL CANDIDATE:

The ideal candidate combines practical AI/ML and data science experience with strong statistical reasoning, operations research skills, and programming ability. They have demonstrated experience using Python and SQL to analyze complex datasets, develop and evaluate machine learning models, and create reusable, tested, and well-documented code. They can independently plan and complete analytical projects, choose appropriate methods for the available data, and communicate findings and recommendations clearly to operational subject matter experts and senior leaders.Experience with data engineering for analytics and machine learning is desirable, including building data pipelines and extract, transform, and load (ETL) workflows; integrating data from multiple sources; validating data quality; and implementing relational or dimensional data models. Experience with Databricks, Apache Spark/PySpark, and Delta Lake, or comparable technologies, is particularly relevant.

How you will be evaluated

You will be evaluated for this job based on how well you meet the qualifications above.

In order to qualify for this position, your resume must provide sufficient experience and/or education, knowledge, skills, and abilities to perform the duties of the specific position for which you are being considered. Resumes are restricted to no more than 2 pages. Illegible/unreadable resumes will not be considered. Your resume is the key means we have for evaluating your skills, knowledge, and abilities as they relate to this position. Therefore, we encourage you to be clear and specific when describing your experience.

As vacancies occur, the Human Resources Office will review your resume to ensure you meet the hiring eligibility and qualification requirements listed in this flyer. You will be rated based on the information provided in your resume, along with your supporting documentation.

If selected, you may be required to provide additional supporting documentation.

If after reviewing your resume and supporting documentation, a determination is made that you inflated your qualifications and/or experience, you may be found ineligible/not qualified.

Please follow all instructions carefully. Errors or omissions may affect your rating or consideration for employment.

All qualification requirements must be met before being considered for any vacancies.