Description
Overview Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted. The Joint, Office of the Secretary of Defense, Interagency Division provides expert support services to a range of customers spanning across the Department of Defense, Federal Civilian, and international markets. JOID provides a diverse portfolio of analytical and programmatic capabilities to help our customers make informed decisions on their most challenging issues. SPAs NATO Allied Command Transformation Group within JOID provides capability development, portfolio management, program management, quality management, cost estimation analysis, standardization, reporting, software solutions and information management, and capability management support. We also provide an improved capability requirements capture process, including the generation, documentation and tracing of user requirements, with appropriate technical scrutiny, over the entire lifecycle of the requirements from capability definition through capability realization and capability usage. We have a near-term need for an AI/ML Engineer to provide onsite support out of Allied Command Transformation (NATO) in Norfolk, VA. Responsibilities The candidate will support the Capability Development Directorate in the process of implementing measures for improved capability development planning and management, including the way it collects, manages, analyses and reports on capability development and delivery information. Support both legacy and current through-work on AI/ML model development, advanced analytics integration, data preparation, and feature engineering. Apply knowledge of cloud-based AI/ML engineering and apply model lifecycle management, responsible AI practices, use of automation and optimization, and other techniques. Support stakeholder engagement and knowledge transfer, and ensure work is secure and meets all complaince requirements. Qualifications Required: Bachelor's degree in Data Science, Computer Science, Mathematics, Engineering, Statistics, or a related quantitative discipline. 8+ years of progressive professional experience in data science, advanced analytics, and/or machine learning engineering, including experience delivering operational analytics or decision-support solutions in complex enterprise environments. Active NATO or National SECRET clearance. Demonstrated expertise in machine learning and statistical modeling, including development, training, validation, and deployment of models supporting forecasting, risk analysis, performance assessment, or decision support across business or capability lifecycles. Demonstrated experience designing and operating automated data pipelines, including ETL/ELT workflows, feature engineering, and data transformation processes to support analytics and AI/ML workloads. Demonstrated professional experience with cloud-based analytics and AI/ML platforms, including deployment and operation of models and data pipelines in secure, scalable cloud environments. Demonstrated experience integrating AI/ML solutions into enterprise analytics tools, dashboards, or reporting platforms to support operational use by analysts and decision-makers. Demonstrated experience with model lifecycle management, including performance monitoring, retraining strategies, version control, documentation, and optimization for production environments. Demonstrated experience working within governed or regulated environments, including adherence to data governance, security, and compliance requirements relevant to defence, security, or other highly regulated domains. Demonstrated ability to collaborate across multidisciplinary teams, including analysts, data engineers, platform engineers, and system administrators, to deliver interoperable, production-ready analytics solutions. Demonstrated ability to communicate complex analytical and AI/ML concepts clearly to both technical and non-technical stakeholders, supporting effective adoption and operational use of delivered solutions. Demonstrated proficiency in English as defined in STANAG 6001. Demonstrable proficiency in effective oral and written communication, including briefing and coordinating with business stakeholders. Able to work fully onsite based on client needs.
Qualifications
Required: Bachelor's degree in Data Science, Computer Science, Mathematics, Engineering, Statistics, or a related quantitative discipline. 8+ years of progressive professional experience in data science, advanced analytics, and/or machine learning engineering, including experience delivering operational analytics or decision-support solutions in complex enterprise environments. Active NATO or National SECRET clearance. Demonstrated expertise in machine learning and statistical modeling, including development, training, validation, and deployment of models supporting forecasting, risk analysis, performance assessment, or decision support across business or capability lifecycles. Demonstrated experience designing and operating automated data pipelines, including ETL/ELT workflows, feature engineering, and data transformation processes to support analytics and AI/ML workloads. Demonstrated professional experience with cloud-based analytics and AI/ML platforms, including deployment and operation of models and data pipelines in secure, scalable cloud environments. Demonstrated experience integrating AI/ML solutions into enterprise analytics tools, dashboards, or reporting platforms to support operational use by analysts and decision-makers. Demonstrated experience with model lifecycle management, including performance monitoring, retraining strategies, version control, documentation, and optimization for production environments. Demonstrated experience working within governed or regulated environments, including adherence to data governance, security, and compliance requirements relevant to defence, security, or other highly regulated domains. Demonstrated ability to collaborate across multidisciplinary teams, including analysts, data engineers, platform engineers, and system administrators, to deliver interoperable, production-ready analytics solutions. Demonstrated ability to communicate complex analytical and AI/ML concepts clearly to both technical and non-technical stakeholders, supporting effective adoption and operational use of delivered solutions. Demonstrated proficiency in English as defined in STANAG 6001. Demonstrable proficiency in effective oral and written communication, including briefing and coordinating with business stakeholders. Able to work fully onsite based on client needs.
Responsibilities
The candidate will support the Capability Development Directorate in the process of implementing measures for improved capability development planning and management, including the way it collects, manages, analyses and reports on capability development and delivery information. Support both legacy and current through-work on AI/ML model development, advanced analytics integration, data preparation, and feature engineering. Apply knowledge of cloud-based AI/ML engineering and apply model lifecycle management, responsible AI practices, use of automation and optimization, and other techniques. Support stakeholder engagement and knowledge transfer, and ensure work is secure and meets all complaince requirements.
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