About this role
Job SummaryThis position is located in the Office of Inspector General - Office of Data Analytics and Technology - Data Analytics Directorate. The OIG is an independent office within EPA that helps the agency protect the environment in a more efficient and cost-effective manner. We consist of auditors, program analysts, investigators, and others with extensive expertise. Although we are a part of EPA, Congress provides us with our funding separate from the agency, to ensure our independence.
QualificationsBASIC REQUIREMENTS FOR DATA SCIENTIST: You must have either A or B: Degree: 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. In addition to the basic requirements: You may qualify for the GS-09 grade level, if you possess at least one year of specialized experience equivalent to the GS-07 grade level in the federal sector, or the equivalent in the private sector. Specialized experience is experience that has equipped the candidate with the particular knowledge, skills, and abilities to perform successfully the duties of the position. For this position your specialized experience must demonstrate the following: Creating and modeling data analysis and statistical trends using data pipelines which includes data cleaning, feature engineering, design and implementation of machine learning models, including generative AI and agentic AI solutions, to support projects in Amazon Web Services (AWS) and Microsoft 365 (M365) environments; Creating visualizations for data analysis and findings using business intelligence tools, Link Analysis tools, and Machine Learning (ML) services such as Microsoft PowerBI, ArcGIS Knowledge, ArcGIS Enterprise, and Amazon SageMaker; Developing or optimizing SQL, Python, and R code related to (ML) models, queries, or database operations for efficient data access, processing, and reporting; and Assisting with technical documentation by creating data dictionaries, methodologies, and utilizing version control for traceability of the entire lifecycle of data and analytical models. You may qualify for the GS-11 grade level, if you possess at least one year of specialized experience equivalent to the GS-09 grade level in the federal sector, or the equivalent in the private sector. Specialized experience is experience that has equipped the candidate with the particular knowledge, skills, and abilities to perform successfully the duties of the position. For this position your specialized experience must demonstrate the following: Creating and modeling data analysis and statistical trends using data pipelines which includes data cleaning, feature engineering, design and implementation of machine learning models, including generative AI and agentic AI solutions, to support projects in Amazon Web Services (AWS) and Microsoft 365 (M365) environments; Creating visualizations for data analysis and findings using business intelligence tools, Link Analysis tools, and Machine Learning (ML) services such as Microsoft PowerBI, ArcGIS Knowledge, ArcGIS Enterprise, and Amazon SageMaker; Developing or optimizing SQL, Python, and R code related to (ML) models, queries, and database operations for efficient data access, processing, and reporting; Preparing and maintaining technical documentation including data dictionaries, methodologies, and utilize version control of code for traceability of the entire lifecycle of data used and models produced Evidence of the above specialized experience must be supported by detailed documentation of duties performed in positions held. 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. We will not make assumptions regarding your experience or based on job titles alone. If your resume does not support your questionnaire answers, we will not allow credit for your response(s). 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; 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. You will receive credit for all qualifying experience, including volunteer experience. Applicants must meet the qualifications for this position within thirty (30) days of the closing date of this announcement.
Major DutiesAs a Data Scientist (Direct Hire) GS-1560-09 your typical work assignments may include the following under supervision: At the direction of the Director or Team Lead and using established methods, create and model data analysis and statistical trends using data pipelines which includes data cleaning, feature engineering, design and implementation of machine learning models, including generative AI and agentic AI solutions, to support oversight projects and investigations in the Amazon Web Services (AWS) and Microsoft 365 (M365) environments. At the direction of the Director or Team Lead and using established methods, create visualizations for data analysis and findings using business intelligence tools, Link Analysis tools, and Machine Learning (ML) services such as Microsoft PowerBI, ArcGIS Knowledge, ArcGIS Enterprise, and Amazon SageMaker. At the direction of the Director or Team Lead, review and optimize SQL, Python, and R code related to (ML) models, queries, and database operations for efficient data access, processing, and reporting. Assists with technical documentation by creating data dictionaries, methodologies, and utilizing version control for traceability of the entire lifecycle of data and analytical models. Support data validation, testing, and monitoring of data analyses that support audits, evaluations, and investigations and participate in code reviews, quality assurance, lessons learned, and ensure reproducibility of the analyses. As a Data Scientist (Direct Hire) GS-1560-11 your typical work assignments may include the following under supervision: At the direction of the Director or Team Lead, create and model data analysis and statistical trends using data pipelines which includes data cleaning, feature engineering, design and implementation of machine learning models, including generative AI and agentic AI solutions, to support oversight projects and investigations in the Amazon Web Services (AWS) and Microsoft 365 (M365) environments. At the direction of the Director or Team Lead, create visualizations for data analysis and findings using business intelligence tools, Link Analysis tools, and Machine Learning (ML) services such as Microsoft PowerBI, ArcGIS Knowledge, ArcGIS Enterprise, and Amazon SageMaker. At the direction of the Director or Team Lead, develop or optimize SQL, Python, and R code related to (ML) models, queries, and database operations for efficient data access, processing, and reporting. Prepare and maintain technical documentation including data dictionaries and methodologies, and utilizes version control for traceability of the entire lifecycle of data and models. Support data validation, testing, and monitoring of data analyses that support audits, evaluations, and investigations and participate in code reviews, quality assurance, lessons learned, and ensure reproducibility of the analyses.