Note: The job is a remote job and is open to candidates in USA. Tanaq Technical Services, a division of St. George Tanaq Corporation, delivers enterprise integrated technology solutions and support services to the Federal Government using modern engineering, secure cloud architecture, and emerging AI/ML technologies. The AI Data Scientist will develop and operationalize advanced analytics, machine learning models, predictive simulations, and AI-driven solutions supporting HUD AI/ML initiatives. The role also involves cross-functional collaboration, enterprise AI platform architecture, MLOps, model governance, and responsible AI practices.
Responsibilities
- 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
- 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
- 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
- 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
- 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
Skills
- 5+ years of professional experience in data science, machine learning, advanced analytics, or applied AI
- Demonstrated experience developing and deploying predictive models and machine learning solutions in production environments
- Strong experience with statistical analysis, machine learning algorithms, and data modeling techniques
- Experience working with large-scale datasets and modern data platforms
- Strong programming skills in Python and modern data science frameworks
- Experience working in collaborative Agile or product-focused development environments
- Excellent communication, presentation, and problem-solving skills
- Ability to pass required background screening and obtain/maintain appropriate customer approvals or government clearance, where required
- Must be legally authorized to work in the United States without sponsorship now or in the future
- Candidates must reside in the United States
- An estimated 10-15% annual travel within the U.S. will be required
- Python (Pandas, NumPy, Scikit-learn, TensorFlow and/or PyTorch)
- SQL, NoSQL Databases, Apache Spark, Kafka, Cloud Data Platforms, API Integration
- Predictive Modeling, Statistical Analysis, Simulation & Forecasting, M/L Lifecycle Management, Model Evaluation & Validation, Generative AI & LLM Concepts
- Plotly, Matplotlib, Seaborn
- Git/GitHub/GitLab, MLOps, CI/CD, Reproducible Workflows, Model Governance
- Advanced analytical and critical thinking skills
- Strong business and technical problem-solving ability
- Data-driven decision making
- Cross-functional collaboration and stakeholder engagement
- Communication of complex technical concepts to diverse audiences
- Commitment to responsible and ethical AI practices
- Continuous learning and innovation mindset
- Strong attention to quality, accuracy, and documentation
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field required
- Prolonged periods of sitting at a desk and working on a computer. May need to lift up to 25 pounds occasionally
- Experience with enterprise-scale AI, cloud-based analytics platforms, or advanced AI/ML ecosystems
- Familiarity with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and AI agent frameworks
- Experience supporting federal government, regulated, or highly governed environments
- Knowledge of AI governance, model risk management, privacy, security, and responsible AI frameworks
- Experience with MLOps, CI/CD pipelines, and model monitoring
- Master's degree in Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Computer Science, or related field preferred
- Professional certifications in Data Science, Machine Learning, AI, Cloud Platforms, or related technologies preferred
Benefits
- Remote position
- 10-15% annual travel within the U.S. is required
Company Overview