Hybrid Principal Transportation Data & AI Architect

Battelle

Virginia (MN)

Hybrid

USD 155,000 - 220,000

Full time

14 days+

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Benefits offered by this job

Hybrid work schedule 60% in-office / 4

Tuition assistance

401(k) retirement plan with employer 5

Job summary

Battelle is seeking a Principal Transportation Data & AI Architect for a full-time role in the DC Metro region (Hybrid). The position advances data-informed decision-making through scalable analytics and AI-enabled transportation solutions across federal, state, and commercial clients.

You will lead data architecture, governance, and AI initiatives, transforming transportation data into actionable insights, and guiding enterprise data platforms, federated architectures, and dashboards for

Qualifications

Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, Information Systems, or a related field.
10+ years of experience in data architecture, data engineering, analytics, AI/ML, or related technical disciplines.
Demonstrated experience managing large, complex datasets and enterprise-scale data environments.
Expertise in data governance, data integration, data quality, and metadata management.
Experience developing and deploying machine learning and AI solutions.
Proficiency with Python, SQL, cloud-based data platforms, and modern analytics technologies.
Strong communication and leadership skills with the ability to engage both technical and non-technical stakeholders.
Willingness to travel as required.
Applicants must have authorization to work in the United States. We are unable to sponsor or take over sponsorship of any employment Visa at this time.

Responsibilities

Developing and overseeing advanced analytics, machine learning, and AI applications that support operational decision-making, automation, and system optimization.
Guiding the implementation of AI-enabled transportation solutions, including predictive analytics, intelligent monitoring, and decision support tools.
Designing and implementing enterprise data architectures supporting transportation operations, planning, and performance management.
Leading the development of roadway data ecosystems that integrate data from infrastructure, vehicles, sensors, operational systems, and external partners.
Designing scalable data platforms, pipelines, and federated architectures that enable data sharing across agencies and stakeholders while maintaining local ownership and control.
Establishing data governance, quality, metadata, security, and stewardship frameworks that promote trusted and interoperable data.
Supporting transportation performance measurement initiatives by developing data strategies, dashboards, and analytical frameworks.
Evaluating emerging technologies and standards related to digital infrastructure, connected transportation systems, and artificial intelligence.
Serving as a trusted advisor to clients, program managers, and senior leadership on data and AI strategy.