Data Scientist in Transportation Operations

Description

Are you passionate about transforming the future of transportation? Join the Leidos team at the Saxton Transportation Operations Laboratory (STOL), a USDOT research facility dedicated to enhancing transportation operations, safety, mobility, and environmental sustainability.

As a skilled Data Scientist in Transportation Operations, you will play a pivotal role in FHWA-funded projects that merge AI, data science, and transportation. Your focus will be on developing and deploying AI and ML models for critical applications like vehicle load classification, crash prediction, and creating robust data ecosystems. We are looking for someone with hands-on experience in AI model development, data integration, and strong stakeholder engagement skills. You will have the chance to drive innovation in a dynamic, federally-supported research setting.

Location: McLean, VA (on-site)

Primary Responsibilities

• Conduct thorough data and literature reviews, focusing on AI methods and technologies relevant to freight analytics, traffic safety, and operations.
• Prepare datasets for AI applications, ensuring they are cleaned, normalized, and fused from multiple sources while addressing quality concerns.
• Lead the design, development, and deployment of AI/ML models for transportation applications, including classifying oversized and overweight vehicles and predicting crashes in traffic management centers.
• Assess AI model performance across different conditions and provide insights for improving robustness and scalability.
• Engage stakeholders through workshops and technical briefings to identify AI application insights in transportation.
• Explore and pursue new AI initiatives with state DOTs, contributing to roadmaps and strategies for intelligent transportation systems.
• Collaborate with teams to align projects with FHWA goals, overseeing risk management and compliance.
• Deliver technical leadership through progress reports, risk assessments, and iterative model refinement based on federal feedback.

Required Qualifications

• Bachelor's degree in computer science, Data Science, AI, Electrical Engineering, Transportation Engineering, or related field; Master's or Ph.D. preferred.
• 5+ years of experience in data science and AI/ML, with expertise in machine learning frameworks and techniques.
• Proven skills in data integration and preparation, including handling multimodal data and addressing quality issues.
• Strong analytical abilities with experience in model evaluation metrics.
• Excellent communication skills to present complex AI concepts to diverse audiences.
• Capability to work in a fast-paced research environment, with potential travel up to 20% for stakeholder interactions.
• Eligible for a Public Trust clearance, with residency requirements in the U.S.
• Legal authorization to work in the U.S. without sponsorship.

Preferred Qualifications

• Experience collaborating with state DOTs or federal agencies on AI projects within intelligent transportation systems.
• Hands-on experience in developing AI systems for freight classification or crash prediction.
• Familiarity with transportation-specific data sources and industry standards.
• Knowledge of synthetic data generation and advanced machine learning techniques.
• Project management experience in multi-agency initiatives.
• Publications or presentations in relevant AI or transportation conferences.

Anticipated salary range for this role is $95,000-$130,000

At Leidos, we seek individuals who are eager to break boundaries and build innovative solutions. If you are driven, enthusiastic, and ready to chart the future of transportation, we want to hear from you