Leidos is seeking a Junior Transportation Data Scientist to support FHWA-funded projects at the intersection of AI, data science, and transportation, specifically to develop and deploy AI/ML models for applications such as vehicle load classification and crash prediction in traffic management centers.
Requirements
- Familiarity in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
- Data processing tools (e.g., Pandas, NumPy)
- AI techniques (e.g., deep learning, generative AI like GANs, computer vision)
- Experience in data preparation and integration, including ETL processes, handling multimodal data
- Strong analytical skills with familiarity in model evaluation metrics (e.g., AUC, accuracy, scalability) and testing AI systems under varied conditions
- Prior experience working with state DOTs or federal transportation agencies on AI initiatives
- Familiarity with transportation-specific data sources (e.g., HSIS, SHRP2, NGSIM) and standards (e.g., SAE J2735 for V2X)
Responsibilities
- Assist in conducting data and literature reviews, including targeted searches for AI methods, datasets, and technologies relevant to freight analytics, traffic safety, and operations
- Prepare and integrate datasets for AI use cases, including cleaning, normalizing, enriching, and fusing multi-source data
- Contribute to the design, development, and deployment of AI/ML models for transportation applications, including classifying oversized/overweight vehicles using WIM data and imagery, crash prediction in TMCs, and generating synthetic data for model training
- Evaluate AI model performance under diverse conditions, such as varying data quality levels, and provide recommendations for improving model robustness, scalability, and trustworthiness in real-world transportation environments
- Assist in identifying and pursuing new opportunities with state DOTs for AI initiatives, including contributions to developing roadmaps, proposals, and implementation strategies for AI in ITS
- Collaborate with cross-functional teams to ensure project alignment with FHWA goals, including risk management, quality assurance, and compliance with federal standards
- Contribute to monthly progress reporting, risk mitigation, and iterative model refinement based on federal feedback
Other
- Bachelor's degree in computer science, Data Science, Artificial Intelligence, Electrical Engineering, Transportation Engineering, or a related field; Master's preferred
- Ability to work in a fast-paced, research-oriented environment with travel up to 20% for stakeholder meetings and site visits
- Ability to obtain and maintain a Public Trust clearance (which includes three years of immediate residency in the US)
- All applicants must be legally authorized to work in the United States without company sponsorship
- Excellent communication and collaboration skills, with experience in stakeholder engagement, technical reporting, and presenting complex AI concepts to non-technical audiences
