Data Scientist - AI Engineer
$85.45k - $158.32kOffice of Inspector General USPS
Summary *PLEASE NOTE THAT THIS VACANCY ANNOUNCEMENT IS ONLY OPEN TO CURRENT UNITED STATES POSTAL SERVICE OFFICE OF INSPECTOR GENERAL, UNITED STATES POSTAL SERVICE, UNITED STATES POSTAL INSPECTION SERVICE AND POSTAL REGULATORY COMMISSION EMPLOYEES. OTHER APPLICANTS WILL NOT BE CONSIDERED. This announcement provides the opportunity for a reassignment/promotion to Data Scientist - AI Engineer position in the Research and Insights Solution Center located in Arlington, Virginia. Learn more about this agency Duties Help The Research and Insights Solution Center (RISC) is the chief data and research component of the OIG, comprised of data scientists, data analysts, programmatic subject matter experts, geographic information system professionals, data engineers, research specialists, economists, and public policy analysts. Our analytics group offers the opportunity to drive value to the organization by designing and developing analytical solutions for auditors, investigators, and researchers. The RISC analytics group is currently seeking an experienced Data Scientist - AI Engineer who will be responsible for researching, assessing, evaluating, and realizing useful and valuable emerging technologies and techniques that can progress the analytic and artificial intelligence (AI) capabilities and offerings across OIG. This position will provide thought leadership for RISC, in enabling data science work that requires application of data mining techniques, model development, statistical analysis, predictive analytics, text analytics, machine learning, artificial intelligence, and other emerging technologies, to support OIG's oversight of USPS through audits, white papers, and investigations. Bring your skills and voice to our team! NOTE: This is a TERM appointment, with an initial term of two years, with the possibility of three additional extensions of up to one-year each. The position may be extended further without competition. Candidates will be evaluated on the skills that they possess that are directly related to the duties of the position and the experience, education and training that indicate the applicant's ability to acquire the particular knowledge and skills needed to perform the duties of the position. Only those candidates who meet all qualification and eligibility requirements and who submit the required information by 11:59 PM EST on 06/11/2026 will be considered. The USPS OIG uses a Pay Banding system, which is equivalent to the Federal GS scale. Grade and salary determinations will be made based upon a candidate's education and professional experience. This position is being advertised at the Journey Band level, equivalent to a GS-11 - GS-13. The salary range for this position is $85,447.00 - $158,322.00. The salary figures include locality pay. Promotion potential to a GS-13 is at management's discretion. Please note that the duties and responsibilities associated with this position may vary based upon the agency's needs at the time of hire. The following description of major duties and responsibilities is only intended to give applicants a general overview of the expectations. The following description of major duties and responsibilities is only intended to give applicants a general overview of the expectations.
- Infrastructure Tooling & Engineering: Develops scalable infrastructure tooling and cloud-based engineering workflows to support the automated, reproducible deployment of analytics and artificial intelligence pipelines.
- Graph Architecture Integration: Designs, implements, and maintains the core graph database ecosystem, focusing on relationship mapping to uncover hidden networks and anomalies within complex datasets.
- Generative AI & LLM Customization: Directs the integration, prompt engineering, orchestration, and fine-tuning of commercial and open-source Large Language Models (LLMs) to optimize the extraction of structured data from unstructured formats.
- Model Validation & MLOps Monitoring: Builds shared validation tools and operational systems to track machine learning model performance, detect data drift, and address live deployment anomalies.
- Software Engineering Standards: Applies rigorous modern software engineering practices, including continuous integration and continuous deployment (CI/CD) pipelines, to govern the end-to-end model lifecycle.
- Algorithmic Product Creation: Architects advanced analytics products and writes specialized software code to implement complex analytical frameworks targeted at priority organizational objectives.
- Testing, Safety, & Compliance: Executes comprehensive testing protocols for AI integrations to ensure full compliance with performance baselines, security controls, and federal alignment standards.
- Community Upskilling & Planning: Partners with internal leadership to perform training needs assessments and execute strategic workforce development plans that build code-driven analytics capabilities across the agency.
- Emergent Technology Prototyping: Researches the frontiers of data science, commercial APIs, and knowledge management to perform rapid prototyping and rigorous experimentation on novel technical workflows.
- Cross-Functional Synergy & Adoption: Facilitates collaborative project delivery across technical boundaries, coordinates with external providers, and creates accessible user documentation to accelerate system adoption.
- Must be a U.S. citizen
- Must be able to pass a drug screening
- Must be able to pass a background investigation
- Must be able to obtain and maintain Moderate Background Investigation security clearance
- Must be able to obtain and maintain a government-issued credit card
- May be required to successfully complete a 12-month probationary period
- Bachelor's degree from an accredited college or university in Computer Science, Data Science, Information Technology, Engineering, Mathematics, Statistics, or a closely related quantitative field.
- Applicants must have one (1) year of specialized experience equivalent to the next lower grade level demonstrating the following technical competencies:
- Programming for AI/Data Science: Experience using modern programming languages standard to data science and AI engineering (Python required; experience with SQL, Scala, or Rust is a plus) to build data pipelines and integrate analytics applications.
- Generative AI & LLM Frameworks: Experience developing, configuring, or integrating machine learning models and Large Language Model (LLM) orchestration frameworks (e.g., LangChain, LlamaIndex, Hugging Face, or commercial AI APIs like Azure OpenAI).
- Enterprise Data & Tooling workflows: Experience utilizing collaborative notebooks, cloud-native platforms, or data management tools (e.g., Databricks, Jupyter, Copilot Studio, or Gemini) for experiment tracking, workflow automation, or model management.
- Relationship & Graph Data Structures: Practical, hands-on experience utilizing or configuring graph databases (e.g., Neo4j, Memgraph) or relational database architectures to map and analyze complex data connections.
- Knowledge of the U.S. Postal Service
- Experience in web app development utilizing front and back-end languages, libraries, and frameworks (e.g. HTML5/CSS, JavaScript, Typescript, jQuery, Bootstrap, Angular, Flask, Django, REST/SOAP APIs)
- Experience with and an understanding of DevOps pipelines and familiarity with the principles of continuous integration and continuous deployment (CI/CD) practices
- Practical experience with cloud platforms such as Azure (preferred), AWS, or GCP
- Business Requirements & ML Translation: Ability to capture complex business requirements and adeptly transform raw organizational data into production-ready machine learning solutions, visualizations, interactive dashboards, and executive presentations.
- LLM Orchestration & RAG Frameworks: Skill in building and scaling Retrieval-Augmented Generation (RAG) architectures using orchestration frameworks (e.g., LangChain, LlamaIndex) and vector databases to safely connect commercial or open-source LLMs to enterprise data sources.
- Model Selection & API Integration: Knowledge of commercial AI APIs (e.g., Azure OpenAI) and open-source foundation models (e.g., Llama, Mistral), with the ability to evaluate model trade-offs regarding context window constraints, latency, cost, and hosting infrastructure.
- Advanced Programming & Core Tooling: Mastery of Python programming and analytical toolsets (e.g., Databricks, Neo4j, Power BI) to manage data engineering pipelines, implement advanced prompt engineering techniques, and enable function calling/agentic workflows.
- LLM Evaluation, Guardrails, & Security: Skill in implementing validation frameworks to evaluate model outputs for accuracy, bias, and faithfulness (mitigating hallucinations), alongside deploying safety guardrails, alignment techniques, and data privacy controls.
- Pipeline Automation & Scalability: Ability to design, implement, and maintain scalable, reliable, and secure data pipelines and MLOps architectures using containerization and continuous integration/continuous deployment (CI/CD) workflows.
- Technical Communications & Briefings: Strong ability to provide structured technical briefings, white papers, and presentations both orally and in writing to clearly communicate complex AI products, model limitations, and strategic recommendations to executives, technical peers, and law enforcement components.
- Agile Frameworks & LLMOps Delivery: Ability to set goals, prioritize project backlogs, and deliver high-quality code in an efficient manner applying Agile, DevOps, or LLMOps practices for model monitoring and continuous integration/deployment (CI/CD).
Vacancy posted 19 hours ago
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