AI/ML Data Scientist

About this role

Description

The AI/ML Data Scientist will work closely with mission stakeholders, business process analysts, data analysts, AI/ML engineers, automation engineers, enterprise architects, data engineers, cybersecurity personnel, and program leadership to identify high-value use cases, assess data readiness, develop predictive and prescriptive analytics solutions, support rapid MVP pilots, and transition successful solutions toward enterprise-scale implementation.

The role will support TRT's "Start Small, Move Fast" approach by rapidly evaluating whether AI is appropriate for a mission problem, developing and testing prototypes, measuring performance and mission value, and helping mature successful solutions for operational use.

Primary Responsibilities

AI/ML Solution Development

• Design, develop, test, and evaluate AI/ML solutions supporting Coast Guard mission and business operations.

• Build predictive, prescriptive, classification, anomaly detection, NLP, generative AI, and other advanced analytical solutions.

• Develop, train, tune, and validate machine learning models that improve operational decision-making, workforce productivity, and mission effectiveness.

• Support AI-enabled MVPs, technical demonstrations, automation pilots, and rapid experimentation efforts.

• Evaluate commercial, Government, and open-source AI/ML models and tools for mission applicability.

Data Science and Analytics

• Conduct exploratory data analysis, statistical modeling, data mining, and advanced analytics using structured and unstructured data.

• Identify trends, patterns, anomalies, and operational insights to support Coast Guard leadership decisions.

• Establish model baselines, performance metrics, acceptance criteria, and test methodologies.

• Assess model accuracy, reliability, false-positive/false-negative rates, bias, limitations, and operational suitability.

• Develop dashboards, visualizations, analytical products, and performance measures supporting enterprise transformation initiatives.

• Establish repeatable data science methodologies, analytical standards, and best practices.

Data Readiness, Engineering, and Integration

• Conduct data readiness assessments covering availability, ownership, quality, completeness, lineage, authoritative sources, and accessibility.

• Clean, normalize, transform, and prepare structured and unstructured datasets for AI/ML analysis.

• Diagnose data-quality issues and recommend corrective actions.

• Support development and optimization of data pipelines, ETL processes, and reusable analytical data models.

• Support integration of data from multiple Coast Guard systems, repositories, and enterprise data platforms.

• Collaborate with data engineers and AI/ML engineers to transition successful prototypes into scalable production environments.

Automation and Digital Transformation

• Support automation opportunity assessments, feasibility analyses, and pilot evaluations.

• Collaborate with automation engineers to integrate AI/ML capabilities into workflow automation, ServiceNow, Power Platform, Appian, Salesforce, and other approved enterprise platforms.

• Participate in business process reengineering efforts and identify opportunities to reduce manual effort through AI, automation, and advanced analytics.

• Support intelligent document processing, classification, entity extraction, summarization, forms digitization, workflow generation, and AI-assisted process automation.

Mission Modeling and Decision Support

• Support mission modeling and simulation initiatives that evaluate mission execution, staffing models, operational impacts, and technology alternatives.

• Develop analytical models supporting scenario planning, operational experimentation, forecasting, and trade-space analysis.

• Translate analytical outputs into actionable recommendations for Coast Guard leadership.

• Support data-driven decision advantage by connecting operational requirements, mission outcomes, and analytical results.

AI Governance, Security, and Responsible Use

• Work with ISSO and ISSE personnel to address cybersecurity, data sensitivity, privacy, access control, and authorization requirements.

• Support responsible AI practices, including human-in-the-loop decision processes, explainability, monitoring, and documentation of model limitations.

• Document assumptions, methodologies, model risks, test results, and lessons learned.

• Support ATO/cATO-related reviews and technical security documentation as required.

Agile Development and Collaboration

• Participate in Agile planning, backlog refinement, sprint reviews, demonstrations, release activities, and user feedback sessions.

• Work with product owners, developers, analysts, architects, engineers, and mission stakeholders to translate use cases into AI/ML solutions.

• Support technical demonstrations and stakeholder briefings.

• Help measure user adoption, operational impact, workload reduction, and "minutes back to mission."

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Artificial Intelligence, Engineering, Information Systems, Operations Research, or related technical field and 8 - 12 years of prior relevant experience or Masters with 6 - 10 years of prior relevant experience

• 8+ years of experience in data science, machine learning, artificial intelligence, advanced analytics, or related disciplines.

• Experience developing, evaluating, and deploying machine learning models.

• Strong proficiency with:
• Python

• SQL

• Scikit-Learn

• TensorFlow and/or PyTorch

• Hugging Face or similar AI/ML frameworks

• Experience with predictive analytics, statistical analysis, data mining, and model evaluation.

• Experience working with large, complex, structured and unstructured datasets.

• Experience developing Generative AI and Large Language Model solutions.

• Experience with Retrieval Augmented Generation architectures.

• Experience…