Prediction & Evaluation Technical Lead
About The Position
The National Reconnaissance Office (NRO) is seeking a Prediction and Evaluation Technical Lead for the Ground Enterprise Directorate's Integrated Intelligence System Program Office (GED/I2SPO). The selected candidate will lead the Multi-INT Prediction and Model Evaluation function and establish a dedicated program office to develop, integrate, evaluate, and operationalize forecasting and prediction models across I2SPO portfolio missions. The work will mature object and behavior prediction capabilities that support object custody, collection effectiveness, situational awareness, collection optimization, and overhead tasking. The lead will translate operational forecasting gaps into a development roadmap and establish technical infrastructure—including a test harness, APIs, and integration standards—to evaluate and deploy prediction capabilities. The role serves as the primary interface among internal model-development teams, compute infrastructure providers, and external forecasting providers, and as the technical authority for selecting forecasting models suited to particular situations and purposes. This is a full-time, non-supervisory federal position at the GG-11 through GG-13 levels, located onsite in Chantilly, Virginia. Telework is unavailable. Applicants must be U.S. citizens and able to obtain and maintain a TS/SCI clearance; pre-employment and periodic drug testing and polygraph examinations apply. Overtime and travel may be required. The announcement is open from October 16, 2026, through October 23, 2026.
Requirements
- Bachelor's degree in a STEM field (Science, Technology, Engineering, or Mathematics).
- Knowledge of forecasting and prediction methodologies, machine learning algorithms, and model evaluation techniques.
- Experience leading technical programs or projects involving algorithm development and operational integration.
- Understanding of software development practices sufficient to define technical architectures and integration requirements.
- U.S. citizenship.
- Ability to obtain and maintain a TS/SCI security clearance.
- Applicants must be able to meet pre-employment and periodic drug-testing and polygraph-examination requirements.
Nice To Haves
- Master's degree in a relevant technical field.
- Experience with maritime tracking, object custody, or geospatial prediction applications.
- Experience developing performance metrics and evaluation frameworks for ML/AI models.
- Knowledge of API design and microservices architectures.
- Experience with test automation and continuous evaluation frameworks.
- Agile program management experience.
- Cloud deployment experience with AWS or Azure.
- Experience integrating third-party algorithms or COTS/GOTS capabilities into operational systems.
Responsibilities
- Establish and lead the Multi-INT Prediction and Model Evaluation Program.
- Develop and maintain a forecasting and prediction capability roadmap that guides model-development priorities within UDE/MAC and integrates third-party forecasters.
- Design and oversee development of a test harness for rapid forecasting-model comparison and evaluation, producing live operational metrics to measure performance and identify capability gaps.
- Survey the forecasting community and industry to assess technology maturity, integration approaches, domain applicability, and performance benchmarks.
- Lead development of Forecasting Interface Control Documents (ICDs) and integration standards for communication with CIP tools, orchestration functions, and collection systems.
- Serve as the technical authority for forecasting and prediction model selection, including enabling automatic selection of the best forecaster for a particular situation or purpose.
- Coordinate integration of forecasting capabilities across the object custody ecosystem and align them with CIP integration requirements and overhead tasking workflows.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
