Data Scientist (Direct Hire)

Environmental Protection Agency; Washington (District of Columbia); On-site; USD 90,000 - 120,000; Full time

Job summary

The Environmental Protection Agency seeks a Data Scientist to join the Office of Inspector General, Data Analytics Directorate, to build data pipelines, models, and visualizations supporting audits and investigations. You will work with AWS and M365 environments, review code, and document methodologies for traceability.

The role includes preparing data dictionaries, ensuring reproducibility, and applying ML techniques including generative/agentic AI where appropriate, in a federally governed

Qualifications

• Experience designing data pipelines and ML models.
• Proficiency in SQL, Python, and R for data tasks.
• Ability to create visualizations using BI and GIS tools.
• Experience with data validation, testing, and reproducibility.

Responsibilities

• Create and model data analysis and statistical trends using data pipelines.
• Develop visualizations with BI tools and ML services such as PowerBI and SageMaker.
• Review and optimize SQL, Python, and R code for efficient data access.
• Document data dictionaries, methodologies, and version control for traceability.
• Support data validation, testing, and monitoring for audits and investigations.

Skills

Data analysis

Statistics

Machine learning

Data visualization

Python

R

SQL

AWS

Tools

PowerBI

ArcGIS Knowledge

ArcGIS Enterprise

Amazon SageMaker

SQL

Python

R

AWS

Job description

Summary

This 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.

Major Duties

As 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.