Journeyman AI/ML Data Scientist

• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Artificial Intelligence, Engineering, Information Systems, Operations Research, or a related technical field.\n
• 0-2 years of experience in data science, machine learning, artificial intelligence, advanced analytics, or a related discipline.\n
• Foundational experience developing, evaluating, or supporting machine learning models.\n

• Working knowledge of: \n \n

• Python\n
• SQL\n
• Scikit-Learn\n
• TensorFlow and/or PyTorch\n

• Hugging Face or similar AI/ML frameworks\n \n

• Foundational experience with predictive analytics, statistical analysis, data mining, and model evaluation.\n
• Experience working with structured and/or unstructured datasets.\n
• Exposure to Generative AI, Large Language Models, or prompt engineering.\n
• Exposure to Retrieval Augmented Generation concepts or architectures.\n
• Familiarity with cloud and data platforms such as AWS, Azure, GovCloud, Databricks, Apache Spark, Hadoop, Kafka, Airflow, or AWS Glue.\n
• Ability to support integration of AI/ML capabilities with APIs, workflow tools, enterprise applications, or data services.\n
• Strong written and verbal communication skills.\n
• U.S. Citizenship required.\n
• Ability to obtain and maintain a DHS Public Trust.\n, * Exposure to agentic AI, embeddings, vector databases, or AI orchestration frameworks.\n
• Familiarity with ServiceNow, Power Platform, Appian, Salesforce, or similar enterprise workflow environments.\n
• Experience supporting Agile, rapid prototyping, hackathons, academic projects, or MVP-style delivery environments.\n

n Leidos is seeking a Journeyman AI/ML Data Scientist. The \nJourneyman AI/ML Data Scientist will support the Decision Advantage team in identifying, evaluating, and developing AI/ML and data analytics solutions that address Coast Guard mission and business needs. This role will work under the guidance of senior data scientists, AI/ML engineers, data engineers, automation engineers, business process analysts, cybersecurity personnel, enterprise architects, and program leadership to support use case discovery, data readiness assessments, prototype development, model testing, and MVP pilot activities.\n \n \nPrimary Responsibilities\n \n \nAI/ML Solution Development\n \n \n

• Support the design, development, testing, and evaluation of AI/ML solutions for Coast Guard mission and business operations.\n
• Assist with development of predictive, classification, anomaly detection, NLP, generative AI, and other analytical solutions.\n
• Support training, tuning, validation, and documentation of machine learning models under senior technical guidance.\n
• Assist with AI-enabled MVPs, technical demonstrations, automation pilots, and rapid experimentation efforts.\n
• Research and evaluate commercial, Government, and open-source AI/ML models and tools for potential mission use.\n

\n \nData Science and Analytics\n \n \n

• Conduct exploratory data analysis using structured and unstructured datasets.\n
• Identify basic trends, patterns, anomalies, and insights to support decision-making.\n
• Support the development of model baselines, performance measures, acceptance criteria, and test methods.\n
• Assist in evaluating model accuracy, reliability, limitations, and operational suitability.\n
• Develop dashboards, visualizations, analytical summaries, and performance measures.\n
• Follow repeatable data science methods, analytical standards, and team best practices.\n

\n \nData Readiness, Engineering, and Integration\n \n \n

• Support data readiness assessments, including data availability, quality, completeness, lineage, ownership, and accessibility.\n
• Clean, normalize, transform, and prepare data for AI/ML analysis.\n
• Help diagnose data-quality issues and document recommended corrective actions.\n
• Support development of data pipelines, ETL processes, and reusable analytical datasets.\n
• Assist with integration of data from Coast Guard systems, repositories, and enterprise platforms.\n
• Work with data engineers and AI/ML engineers to help move successful prototypes toward scalable implementation.\n

\n \nAutomation and Digital Transformation\n \n \n

• Support automation opportunity assessments, feasibility analyses, and pilot evaluations.\n
• Assist automation engineers in identifying where AI/ML could enhance workflow automation or digital transformation efforts.\n
• Support AI/ML integration with approved enterprise platforms such as ServiceNow, Power Platform, Appian, Salesforce, or similar tools.\n
• Participate in business process analysis activities to identify opportunities to reduce manual effort.\n
• Support intelligent document processing, classification, entity extraction, summarization, forms digitization, and AI-assisted workflow improvements.\n

\n \nMission Modeling and Decision Support\n \n \n

• Support mission modeling and simulation efforts that evaluate mission execution, staffing, operational impacts, and technology alternatives.\n
• Assist in developing analytical models for scenario planning, forecasting, operational experimentation, and trade-space analysis.\n
• Help translate analytical outputs into clear findings and recommendations for technical and non-technical audiences.\n
• Support data-driven decision-making by connecting operational needs, mission outcomes, and analytical results.\n

\n \nAI Governance, Security, and Responsible Use\n \n \n

• Work with senior team members and cybersecurity personnel to address data sensitivity, privacy, access control, and security requirements.\n
• Support responsible AI practices, including human-in-the-loop review, explainability, model monitoring, and documentation of limitations.\n
• Document assumptions, methodologies, model risks, test results, and lessons learned.\n
• Support ATO/cATO-related documentation and reviews, as needed.\n

\n \nAgile Development and Collaboration\n \n \n

• Participate in Agile planning, backlog refinement, sprint reviews, demonstrations, release activities, and user feedback sessions.\n
• Work with product owners, developers, analysts, architects, engineers, and mission stakeholders to support AI/ML use case delivery.\n
• Prepare technical documentation, demonstration materials, and stakeholder briefing inputs.\n
• Help measure user adoption, operational impact, workload reduction, and “minutes back to mission.”\n