AI/ML SME in Springfield, Virginia at Diaconia LLC

Position Overview

Diaconia is seeking an AI/ML SME to support a federal civilian customer's enterprise data modernization program. This role supports a mission-critical, nationwide case-management and intelligence-analysis platform that integrates enterprise data, analytics, reporting, enterprise search, AI/ML-enabled enrichment, and operational workflows across multiple regions.

The AI/ML SME will serve as the analytic team lead for AI/ML initiatives that enrich enterprise data and improve analytical capabilities across mission data holdings. The role will support development, enhancement, training, validation, deployment, and maintenance of AI/ML models, with emphasis on entity extraction, relationship identification, unstructured data processing, model evaluation, model monitoring, and integration of AI/ML outputs into the broader data ecosystem.

Key Responsibilities

- Serve as the AI/ML subject matter expert and analytic team lead for data science initiatives.

- Lead analytic modernization efforts across enterprise data and mission analytics environments.

- Provide technical and management leadership on major tasks and technology assignments.

- Establish goals and plans that meet project objectives; supervise others as needed.

- Evaluate enterprise data holdings and identify data sources suitable for AI/ML model development, enrichment, and mission analytics.

- Develop, train, test, tune, validate, and deploy machine learning and AI models aligned to approved business use cases.

- Support supervised and unsupervised learning, natural language processing, entity extraction, relationship identification, and unstructured data manipulation.

- Design and implement ETL processes to extract, clean, standardize, and prepare source data for model training and deployment.

- Support development and delivery of high-quality data systems, reports, analytical products, and features.

- Support O&M for existing data systems, including enterprise data warehouse integrations, enterprise reporting, enterprise search/OpenSearch, and AI/ML-enabled enrichment.

- Support enterprise reporting via Power BI dashboards and data calls.

- Support enterprise search/OpenSearch capabilities, APIs, and business intelligence functions where AI/ML integration or data enrichment is required.

- Document model assumptions, data inputs, training parameters, validation results, deployment configuration, and reproducibility steps.

- Conduct independent validation of model outputs for accuracy, stability, and bias detection.

- Package and deploy validated models to designated test or production environments.

- Configure application interfaces, APIs, or automation pipelines required for model operations.

- Establish model monitoring and retraining mechanisms to detect performance drift.

- Prepare AI business case summaries, leadership briefings, and technical documentation explaining model purpose, value proposition, expected outcomes, and integration opportunities.

- Coordinate with data engineering, reporting, search, cloud, security, and product owner teams to integrate AI/ML capabilities into the broader enterprise data ecosystem.

- Support modernization across cloud and non-cloud technology stacks.

Minimum Requirements:

- U.S. Citizenship required.

- Active U.S. government Secret clearance or higher required at proposal submission.

- Bachelor's degree and 10+ years of related experience required.

- Four additional years of relevant experience may be substituted in lieu of a Bachelor's degree.

- A Master's degree or higher may reduce the required experience by two years.

- 10+ years of overall related professional experience in data science, analytics, AI/ML, data engineering, enterprise data, or mission analytics environments.

- 5+ years of in-depth experience with at least one analytical or statistical language, such as Python, R, or SQL.

- At least 2 years of experience with custom machine learning and AI model training, including supervised and unsupervised learning.

- At least 2 years of Natural Language Processing expertise focused on unstructured data.

- 3+ years of experience with SQL database development, SQL coding, or SQL-based analytical work.

- 2+ years of experience with data visualization tools.

- 2+ years of experience manipulating unstructured data.

- Experience developing, testing, validating, deploying, documenting, and maintaining AI/ML models.

- Experience supporting enterprise data, reporting, search, O&M, modernization, or cloud-enabled analytics environments.

-Must be able to be ON SITE 3 days or as required by the client.

- Occasional OCONUS travel may be required

Preferred Qualifications

- Educational background in Data Science or a related technical field.

- Experience with federal civilian, law enforcement, investigative, intelligence, or sensitive mission data.

- Experience with entity extraction, entity resolution, relationship analysis, or enrichment of large unstructured datasets.

- Experience integrating model outputs into enterprise search, reporting, data warehouse, or analytics platforms.

- Experience with model monitoring, retraining, performance drift detection, and responsible AI validation practices.

- Experience supporting Agile Scrum delivery and documenting work in Azure DevOps or similar tools.