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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI/ML solution design, development, and evaluation, with a strong foundation in machine learning model training and predictive analytics. Proficient in data analysis, integration of AI capabilities, and effective communication of technical findings to diverse audiences.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProgrammingPredictive AnalyticsData AnalysisAgile Methodologies
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningArtificial IntelligenceStatistical AnalysisData MiningModel EvaluationNLPGenerative AIData CleaningETL ProcessesExploratory Data Analysis
Soft Skills
Strong Communication SkillsCollaborationProblem-Solving
Tools & Technologies
Scikit-LearnTensorFlowPyTorchHugging FaceAWSAzureServiceNowPower PlatformAppianSalesforce
Certifications & Qualifications
DHS Public Trust
Industry Keywords
Data ScienceMachine LearningAI/ML IntegrationFederal AgenciesAgile Planning
Tech Stack
Tools & technologiesAirflowApacheAWSAzureCloudCyber SecurityETLHadoopKafkaPythonPyTorchScikit-LearnServiceNowSparkSQLTensorflow
About the role
Key responsibilities & impact- Support the design, development, testing, and evaluation of AI/ML solutions for Coast Guard mission and business operations.
- Assist with predictive, classification, anomaly detection, NLP, generative AI, and other analytical solutions.
- Support machine learning model training, tuning, validation, and documentation under senior technical guidance.
- Assist with AI-enabled MVPs, technical demonstrations, automation pilots, and rapid experimentation.
- Research and evaluate commercial, Government, and open-source AI/ML models and tools.
- Conduct exploratory data analysis using structured and unstructured datasets.
- Identify trends, patterns, anomalies, and insights to support decision-making.
- Develop model baselines, performance measures, acceptance criteria, test methods, dashboards, visualizations, and analytical summaries.
- Support data readiness assessments, data cleaning, normalization, transformation, data pipelines, ETL processes, reusable analytical datasets, and system integration.
- Support automation assessments and AI/ML integration with enterprise platforms such as ServiceNow, Power Platform, Appian, and Salesforce.
- Participate in business process analysis, intelligent document processing, classification, entity extraction, summarization, forms digitization, and AI-assisted workflow improvements.
- Support mission modeling, simulation, scenario planning, forecasting, operational experimentation, and trade-space analysis.
- Translate analytical outputs into findings and recommendations for technical and non-technical audiences.
- Support data sensitivity, privacy, access control, security, responsible AI, human-in-the-loop review, explainability, model monitoring, and ATO/cATO documentation.
- Participate in Agile planning, backlog refinement, sprint reviews, demonstrations, release activities, and user feedback sessions.
- Collaborate with product owners, developers, analysts, architects, engineers, cybersecurity personnel, and mission stakeholders.
- Prepare technical documentation, demonstration materials, stakeholder briefing inputs, and adoption and operational impact measures.
Requirements
What you’ll need- Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Artificial Intelligence, Engineering, Information Systems, Operations Research, or a related technical field.
- 0–2 years of experience in data science, machine learning, artificial intelligence, advanced analytics, or a related discipline.
- Foundational experience developing, evaluating, or supporting machine learning models.
- Working knowledge of Python, SQL, Scikit-Learn, TensorFlow and/or PyTorch, and Hugging Face or similar AI/ML frameworks.
- Foundational experience with predictive analytics, statistical analysis, data mining, and model evaluation.
- Experience working with structured and/or unstructured datasets.
- Exposure to Generative AI, Large Language Models, or prompt engineering.
- Exposure to Retrieval Augmented Generation concepts or architectures.
- Familiarity with cloud and data platforms such as AWS, Azure, GovCloud, Databricks, Apache Spark, Hadoop, Kafka, Airflow, or AWS Glue.
- Ability to support integration of AI/ML capabilities with APIs, workflow tools, enterprise applications, or data services.
- Strong written and verbal communication skills.
- U.S. Citizenship required.
- Ability to obtain and maintain a DHS Public Trust.
- Preferred: internship, academic, or early career experience supporting DHS, USCG, DoD, or other Federal agencies.
- Preferred: exposure to agentic AI, embeddings, vector databases, or AI orchestration frameworks.
- Preferred: familiarity with ServiceNow, Power Platform, Appian, Salesforce, or similar enterprise workflow environments.
- Preferred: experience supporting Agile, rapid prototyping, hackathons, academic projects, or MVP-style delivery environments.