Leidos
Overview
Leidos is seeking a talented
Junior Transportation Data Scientist
at the junior level to support FHWA-funded projects at the intersection of AI, data science, and transportation. This role involves assisting in the development and deployment of AI/ML models for applications such as vehicle load classification using weigh-in-motion data and imagery, crash prediction in traffic management centers, and creating data ecosystems for trustworthy AI. The ideal candidate will have foundational experience in AI model development, data integration, and stakeholder engagement, with a passion for applying AI in state-level transportation initiatives in a federally supported research environment. Location:
This role requires full-time on-site work at the customer site in McLean, VA. Learn about STOL here: STOL information is available on the Highway Research Center’s page.
Primary Responsibilities Assist in conducting data and literature reviews for AI methods, datasets, and technologies relevant to freight analytics, traffic safety, and operations (e.g., sensor fusion, computer vision, multimodal AI).
Prepare and integrate datasets for AI use cases, including cleaning, normalizing, enriching, and fusing multi-source data while addressing quality issues like inconsistency, sparsity, and bias (e.g., traffic logs, imagery, weather, permitting records).
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 and provide recommendations for improving 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.
Assist in identifying and pursuing new opportunities with state DOTs for AI initiatives, including roadmaps, proposals, and implementation strategies for AI in ITS.
Collaborate with cross-functional teams to align projects with FHWA goals, including risk management, quality assurance, and compliance with federal standards.
Contribute to monthly progress reporting and iterative model refinement based on federal feedback.
Required Qualifications Bachelor’s degree in computer science, Data Science, Artificial Intelligence, Electrical Engineering, Transportation Engineering, or a related field; Master’s preferred.
Minimum of one (1) year of professional experience in the transportation space, data science, and AI/ML, with 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).
Experience with transportation-specific data sources (e.g., HSIS, SHRP2, NGSIM) and standards (e.g., SAE J2735 for V2X).
Strong experience in data preparation and integration, including ETL, handling multimodal data (imagery, sensor data, time-series), and addressing data quality challenges.
Strong analytical skills with familiarity in model evaluation metrics (e.g., AUC, accuracy) 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. Ability to travel up to 20% for meetings and site visits.
Ability to obtain and maintain a Public Trust clearance.
All applicants must be legally authorized to work in the United States without company sponsorship.
Preferred Qualifications Experience with state DOTs or federal transportation agencies on AI initiatives, including AI roadmaps, implementations, or evaluations in ITS.
Experience in synthetic data generation, generative AI, or physics-informed ML for transportation applications.
Knowledge of federal AI governance, risk management, and equity considerations in transportation.
Project management experience, including leading AI tasks in multi-agency initiatives or contributing to communities of practice.
Publications or presentations in AI/transportation conferences (e.g., TRB, ITS America).
Salary range familiarity: Anticipated range for this role is $75,000-$100,000, depending on experience.
At Leidos, we don’t want someone who "fits the mold"—we want someone who melts it down and builds something better. This is a role for the restless, the eager, the ones who ask, “what’s next?” before the dust settles on “what’s now.”
Original Posting
December 9, 2025
Pay Range
Pay Range $57,850.00 - $104,575.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation. Other factors may influence offers, including responsibilities, education, experience, and internal market considerations.
About Leidos
Leidos is a technology leader serving government and commercial customers with digital and mission innovations. Headquarters in Reston, VA, with global employees. For more information, visit Leidos.com.
Pay and Benefits
Pay and benefits reflect the importance of compensation in career decisions. Details are available at Leidos careers pages.
Securing Your Data
Beware of fake opportunities. Leidos will never ask for payment-related information during the application process. If you suspect a scam, contact LeidosCareersFraud@leidos.com.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, veteran status, or any other basis prohibited by law. Leidos will also consider qualified applicants with criminal histories consistent with relevant laws.
#J-18808-Ljbffr
Leidos is seeking a talented
Junior Transportation Data Scientist
at the junior level to support FHWA-funded projects at the intersection of AI, data science, and transportation. This role involves assisting in the development and deployment of AI/ML models for applications such as vehicle load classification using weigh-in-motion data and imagery, crash prediction in traffic management centers, and creating data ecosystems for trustworthy AI. The ideal candidate will have foundational experience in AI model development, data integration, and stakeholder engagement, with a passion for applying AI in state-level transportation initiatives in a federally supported research environment. Location:
This role requires full-time on-site work at the customer site in McLean, VA. Learn about STOL here: STOL information is available on the Highway Research Center’s page.
Primary Responsibilities Assist in conducting data and literature reviews for AI methods, datasets, and technologies relevant to freight analytics, traffic safety, and operations (e.g., sensor fusion, computer vision, multimodal AI).
Prepare and integrate datasets for AI use cases, including cleaning, normalizing, enriching, and fusing multi-source data while addressing quality issues like inconsistency, sparsity, and bias (e.g., traffic logs, imagery, weather, permitting records).
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 and provide recommendations for improving 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.
Assist in identifying and pursuing new opportunities with state DOTs for AI initiatives, including roadmaps, proposals, and implementation strategies for AI in ITS.
Collaborate with cross-functional teams to align projects with FHWA goals, including risk management, quality assurance, and compliance with federal standards.
Contribute to monthly progress reporting and iterative model refinement based on federal feedback.
Required Qualifications Bachelor’s degree in computer science, Data Science, Artificial Intelligence, Electrical Engineering, Transportation Engineering, or a related field; Master’s preferred.
Minimum of one (1) year of professional experience in the transportation space, data science, and AI/ML, with 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).
Experience with transportation-specific data sources (e.g., HSIS, SHRP2, NGSIM) and standards (e.g., SAE J2735 for V2X).
Strong experience in data preparation and integration, including ETL, handling multimodal data (imagery, sensor data, time-series), and addressing data quality challenges.
Strong analytical skills with familiarity in model evaluation metrics (e.g., AUC, accuracy) 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. Ability to travel up to 20% for meetings and site visits.
Ability to obtain and maintain a Public Trust clearance.
All applicants must be legally authorized to work in the United States without company sponsorship.
Preferred Qualifications Experience with state DOTs or federal transportation agencies on AI initiatives, including AI roadmaps, implementations, or evaluations in ITS.
Experience in synthetic data generation, generative AI, or physics-informed ML for transportation applications.
Knowledge of federal AI governance, risk management, and equity considerations in transportation.
Project management experience, including leading AI tasks in multi-agency initiatives or contributing to communities of practice.
Publications or presentations in AI/transportation conferences (e.g., TRB, ITS America).
Salary range familiarity: Anticipated range for this role is $75,000-$100,000, depending on experience.
At Leidos, we don’t want someone who "fits the mold"—we want someone who melts it down and builds something better. This is a role for the restless, the eager, the ones who ask, “what’s next?” before the dust settles on “what’s now.”
Original Posting
December 9, 2025
Pay Range
Pay Range $57,850.00 - $104,575.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation. Other factors may influence offers, including responsibilities, education, experience, and internal market considerations.
About Leidos
Leidos is a technology leader serving government and commercial customers with digital and mission innovations. Headquarters in Reston, VA, with global employees. For more information, visit Leidos.com.
Pay and Benefits
Pay and benefits reflect the importance of compensation in career decisions. Details are available at Leidos careers pages.
Securing Your Data
Beware of fake opportunities. Leidos will never ask for payment-related information during the application process. If you suspect a scam, contact LeidosCareersFraud@leidos.com.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, veteran status, or any other basis prohibited by law. Leidos will also consider qualified applicants with criminal histories consistent with relevant laws.
#J-18808-Ljbffr