Leidos is a systems integrator working across science, technology, and engineering to support complex customer missions. Its work spans aviation, defense, energy, government, healthcare, intelligence, science, and space, with capabilities that include artificial intelligence, digital modernization, cyber operations, and integrated mission software. The company also develops solutions such as counter-unmanned aerial systems and electric-vehicle infrastructure for military use. Leidos’ broader profile includes a focus on diversity, equity, inclusion, sustainability, charitable initiatives, and community programs.
AI/ML Data Scientist at Leidos — Remote, United States
Support Leidos’ Coast Guard mission through data science, machine learning, and automation initiatives. Build prototypes, evaluate models, prepare data, and contribute to responsible AI delivery.
Description
- Design, develop, test, and evaluate AI/ML solutions for Coast Guard mission and business operations.
- Contribute to predictive analytics, classification, anomaly detection, NLP, generative AI, and related analytical solutions.
- Train, tune, validate, and document machine learning models under senior technical direction.
- Help deliver AI-enabled MVPs, technical demonstrations, automation pilots, and rapid experiments.
- Assess commercial, government, and open-source AI/ML models and tools.
- Perform exploratory analysis across structured and unstructured data.
- Surface trends, patterns, anomalies, and insights that inform decisions.
- Create model baselines, performance measures, acceptance criteria, test approaches, dashboards, visualizations, and analytical summaries.
- Support data readiness reviews, cleaning, normalization, transformation, pipelines, ETL, reusable datasets, and system integration.
- Assess automation opportunities and integrate AI/ML capabilities with platforms including ServiceNow, Power Platform, Appian, and Salesforce.
- Contribute to process analysis, intelligent document processing, classification, entity extraction, summarization, digitized forms, and AI-assisted workflow improvements.
- Support mission modeling, simulation, scenario planning, forecasting, operational experimentation, and trade-space analysis.
- Convert analytical results into findings and recommendations for technical and non-technical stakeholders.
- Help address data sensitivity, privacy, access control, security, responsible AI, human review, explainability, model monitoring, and ATO/cATO documentation.
- Participate in Agile planning, backlog refinement, sprint reviews, demonstrations, releases, and user feedback sessions.
- Work with product owners, developers, analysts, architects, engineers, cybersecurity teams, and mission stakeholders.
- Produce technical documentation, demonstration materials, briefing inputs, and measures of adoption and operational impact.
Requirements
- 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, plus Hugging Face or a comparable AI/ML framework.
- 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 help integrate AI/ML capabilities with APIs, workflow tools, enterprise applications, or data services.
- Strong written and verbal communication skills.
- U.S. citizenship is 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 with Agile delivery, rapid prototyping, hackathons, academic projects, or MVP-style environments.