Hiring: Transportation Data Scientist (AI Solutions) Company: SLAS (Society for Laboratory Automation and Screening) Location: McLean, VA Job Posted Time: 2026-09-17 00:24:03 Employment Type: Full-time Target Skills & Keywords : AI, Computer Vision, Deep Learning, ETL, GANs, LLM, Machine Learning, NumPy, Pandas, PyTorch, TensorFlow, scikit-learn About the job Experience: •2+ years of professional experience (NON-academic) in data science and AI/ML, with demonstrated familiarity in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), data processing tools (e.g., Pandas, NumPy), and AI techniques (e.g., deep learning, generative AI like GANs, computer vision, LLMs). Required Skills: •Currently located in the United States for the current three consecutive years and be eligible for a Public Trust Clearance. •Assist in conducting data and literature reviews, including targeted searches for AI methods, datasets, and technologies relevant to freight analytics, traffic safety, and operations (e.g., sensor fusion, computer vision, and multimodal AI). •Prepare and integrate datasets for AI use cases, including cleaning, normalizing, enriching, and fusing multi-source data (e.g., traffic logs, imagery, weather, and permitting records) while addressing quality issues like inconsistency, sparsity, and bias. •Contribute to the design, development, and deployment of AI/ML models for transportation applications. •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. •Support stakeholder outreach and engagement, including organizing peer exchanges, workshops, and technical briefings with state DOTs, MPOs, enforcement agencies, and vendors to gather insights on AI applications. •Partner cross-functionally with cross-functional teams to ensure project alignment with USDOT 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. Qualifications: •Master’s degree in computer science, Data Science, Artificial Intelligence, Transportation Engineering, or a related field; Ph.D. preferred. •Strong experience in data preparation and integration, including ETL processes, handling multimodal data (e.g., imagery, sensor data, time-series), and addressing data quality challenges in real-world applications. •Strong analytical skills with familiarity in model evaluation metrics (e.g., AUC, accuracy, scalability) and testing AI systems under varied conditions. •Excellent communication and collaboration skills, with experience in stakeholder engagement, technical reporting, and presenting complex AI concepts to non-technical audiences. •Demonstrated capacity to work in a fast-paced, research-oriented environment with travel up to 20% for stakeholder meetings, site visits, or conference support. •Demonstrated capacity 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. •Prior experience working with state DOTs or federal transportation agencies (e.g., FHWA, USDOT) on AI initiatives, including prototyping and developing AI application in ITS. •Operational familiarity with transportation-specific data sources (e.g., HSIS, SHRP2, NGSIM) and standards (e.g., SAE J2735 for V2X). •Knowledge of federal AI governance, risk management, and equity considerations in transportation. Compensation: •$87,100 - $157,450 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!