AI Data Scientist

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Tanaq Technical Services

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤝 B2B

🏛️ Government

B2B • Government

Tanaq Technical Services is a full service IT firm that provides support to US Federal Agencies. As an Alaskan Native Corporation certified 8(a) business, it specializes in software development and various technology solutions tailored for government clients.

📋 Description

• Analyze, model, and simulate data supporting HUD AI/ML proofs of concept and pilots • Design, develop, and operationalize advanced analytics, machine learning models, predictive simulations, and AI-driven solutions • 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 • Perform feature engineering, data preparation, cleansing, transformation, and quality assessments • Evaluate model performance and refine algorithms to improve accuracy, reliability, and business impact • Support AI-enabled solutions using machine learning, generative AI, LLMs, and emerging AI technologies • Collaborate with AI engineering teams to operationalize models and integrate them into enterprise applications and workflows • Develop 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 SQL, NoSQL, cloud-native platforms, and distributed data environments • Contribute to MLOps, 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 supporting 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 technical and non-technical audiences • Mentor junior team members and contribute to data science best practices and standards

🎯 Requirements

• 5+ years of professional experience in data science, machine learning, advanced analytics, or applied AI • 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 in collaborative Agile or product-focused development environments • Ability to pass required background screening and obtain or maintain customer approvals or government clearance where required • Must be legally authorized to work in the United States without sponsorship now or in the future • Experience with enterprise-scale AI, cloud-based analytics platforms, or advanced AI/ML ecosystems preferred • Familiarity with Generative AI, LLMs, RAG, vector databases, and AI agent frameworks preferred • Experience supporting federal government, regulated, or highly governed environments preferred • Knowledge of AI governance, model risk management, privacy, security, and responsible AI frameworks preferred • Experience with MLOps, CI/CD pipelines, and model monitoring preferred • Python with Pandas, NumPy, Scikit-learn, TensorFlow and/or PyTorch • SQL, NoSQL databases, Apache Spark, Kafka, cloud data platforms, and API integration • Predictive modeling, statistical analysis, simulation and forecasting, ML lifecycle management, model evaluation and validation, and generative AI/LLM concepts • Plotly, Matplotlib, and Seaborn • Git/GitHub/GitLab, MLOps, CI/CD, reproducible workflows, and model governance • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field required • Master's degree and professional certifications preferred • Prolonged periods of sitting at a desk and working on a computer • May need to lift up to 25 pounds occasionally

🏖️ Benefits

• Remote work arrangement • 10–15% annual travel within the U.S. associated with the role • Opportunity to influence enterprise-scale AI initiatives • Opportunity to develop advanced decision-support solutions • Opportunity to help establish best practices for responsible AI, model governance, and data-driven innovation