AI Data Scientist

Overview

Tanaq Technical Services (TTS), a division of St. George Tanaq (SGT)Corporation, is an 8(a) Alaskan Native Small Business that specializes in delivering Enterprise Integrated Technology Solutions and Support Services to the Federal Government. Our teams combine modern engineering, secure cloud architecture, and emerging technologies including AI/ML to improve customer experiences, operational efficiencies, and mission outcomes. We pride ourselves on being Mission Driven and People Focused delivering emerging technologies seamlessly for our clients. People Focused. To learn more about us, visit https://tanaq.com/tanaq-technical-services.

About the Role

We are seeking a highly skilled AI Data Scientist to support the Department of Housing and Urban Development’s Office of the Chief Information Officer (HUD OCIO).

The AI Data Scientist will analyze, model, and simulate data supporting HUD AI/ML proofs of concept and pilots. Additionally, this role will be responsible for designing, developing, and operationalizing advanced analytics, machine learning models, predictive simulations, and AI-driven solutions that support mission-critical business objectives.

The ideal candidate combines deep technical expertise in data science, machine learning, and statistical modeling with the ability to translate complex business problems into scalable, production-ready solutions. You will work across multidisciplinary teams including engineering, AI architects, security professionals, DevOps teams, and business stakeholders to deliver innovative and trustworthy AI capabilities.

This position offers the opportunity to influence enterprise-scale AI initiatives, develop advanced decision-support solutions, and help establish best practices for responsible AI, model governance, and data-driven innovation.

This is a remote position supporting a federal government contract that requires a federal background check and NACI clearance. Candidates must reside in the United States. An estimated 10-15% annual travel within the U.S. will be required.

Responsibilities

Data Science & Machine Learning

• Develop, train, validate, and deploy machine learning models, predictive analytics solutions, and statistical frameworks.
• Design and implement simulations, forecasting models, optimization techniques, and decision-support systems.
• Analyze structured and unstructured datasets to identify patterns, trends, risks, and opportunities.
• Conduct feature engineering, data preparation, cleansing, transformation, and quality assessments to support AI and analytics initiatives.
• Evaluate model performance and continuously refine algorithms to improve accuracy, reliability, and business impact.

AI & Advanced Analytics

• Support the development of AI-enabled solutions utilizing machine learning, generative AI, large language models (LLMs), and emerging AI technologies.
• Collaborate with AI engineering teams to operationalize models and integrate them into enterprise applications and workflows.
• Develop analytical methodologies for risk detection, anomaly identification, behavioral analysis, and decision intelligence.
• Participate in AI experimentation, proof-of-concept development, pilot initiatives, and production deployments.

Data Engineering & Platform Collaboration

• Architect the target-state Enterprise AI Security Platform, including platform components, security services, data flows, APIs, integration patterns, trust boundaries, and deployment models.
• Partner with engineering teams to build scalable data pipelines and analytics workflows.
• Work with enterprise datasets across SQL, NoSQL, cloud-native platforms, and distributed data environments.
• Contribute to MLOps practices, reproducible workflows, version-controlled development, and model lifecycle management.
• Support integration of machine learning solutions with APIs, cloud services, data platforms, and business applications.

Governance, Documentation & Responsible AI

• Document models, assumptions, methodologies, testing procedures, and decision logic.
• Maintain reproducible and auditable workflows to support governance, compliance, and operational excellence.
• Ensure compliance with responsible AI principles, privacy requirements, cybersecurity standards, and ethical AI practices.
• Contribute to model governance, validation frameworks, and risk management activities.

Cross-Functional Leadership

• Collaborate with stakeholders, architects, engineers, UX teams, and business leaders to define analytical requirements and success metrics.
• Present findings, recommendations, and technical concepts to both technical and non-technical audiences.
• Mentor junior team members and contribute to the development of data science best practices and standards.