AI/ML Data Scientist

Leidos

1d • $107,900 - $195,050

About The Position

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.

Requirements

• 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 with cloud and data platforms such as AWS, Azure, GovCloud, Databricks, Apache Spark, Hadoop, Kafka, Airflow, or AWS Glue.
• Experience integrating AI/ML capabilities with enterprise applications, workflow platforms, APIs, or data services.
• Strong written and verbal communication skills with the ability to brief technical and non-technical stakeholders.
• U.S. Citizenship required.
• Ability to obtain and maintain a DHS Public Trust.

Nice To Haves

• Experience supporting DHS, USCG, DoD, or other Federal agencies.
• Experience with agentic AI, embeddings, vector databases, or AI orchestration frameworks.
• Experience with ServiceNow, Power Platform, Appian, Salesforce, or similar enterprise workflow environments.
• Experience with data governance, metadata management, lineage, and authoritative data-source identification.
• Familiarity with NIST AI RMF, NIST 800-53, Zero Trust, ATO/cATO, and Federal AI governance requirements.
• Experience supporting CUI, PII/SPII, or other sensitive Government data.
• Experience supporting Agile, rapid prototyping, or 12-week MVP delivery environments.
• AWS Certified Machine Learning Engineer
• AWS Certified Data Engineer or Solutions Architect
• Microsoft Azure AI Engineer
• Databricks Data Engineer / Machine Learning certification
• Relevant AI/ML, cloud, or data science certification

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.”

Benefits

• If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior