Job DescriptionSOSi is seeking a Data Science Lead to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.
Essential Job Duties:- The contractor shall oversee the development, deployment, and evaluation of predictive and prescriptive analytics to ensure alignment with mission objectives and operational needs.
- The contractor shall establish a structured framework to distinguish data science and data engineering tasks, ensuring the effective allocation of resources and seamless collaboration between teams.
- The contractor shall submit the Predictive Analytics Strategy & Implementation Report, detailing model development progress, algorithm validation, and mission integration.
- The contractor shall coordinate to access compute and storage resources required to support large-scale model training and analytics workloads, including GPU-accelerated environments, high-performance object storage, and parallel data processing capabilities.
- The contractor shall fund usage-based compute and storage costs through inter-task chargeback arrangements, as approved by the Government PM.
Qualifications- Active TS/SCI Clearance.
- Master's degree in Data Science, Artificial Intelligence, Computer Science, or a related field, or;
- Eleven (11) years of equivalent experience in leading AI/ML-driven analytics programs.
- Personnel must have demonstrated experience in developing, deploying, and managing enterprise-level predictive analytics solutions, ensuring governance compliance, and implementing AI/ML models at scale.
- Experience in mission-focused analytics, data-driven decision support, and integration of statistical and machine learning techniques is required.
- Personnel must have experience overseeing sprint-based Agile development cycles and working within cloud-based data science environments such as AWS, Azure, or Databricks.
- Possess the knowledge and capability to lead the development of predictive and prescriptive analytics, ensuring alignment with mission objectives and the integration of AI/ML-driven insights.
- Proficient in advanced machine learning techniques, statistical modeling, and data science methodologies, with expertise in feature engineering, model validation, and data provenance tracking.
- Experience implementing Agile methodologies, managing analytic sprints, and overseeing collaboration between data science and data engineering teams.
- Strong leadership, strategic planning, and stakeholder engagement skills are required to drive mission-focused analytic innovation.
Preferred Qualifications:- Desirable but not required certifications include AWS Certified Machine Learning - Specialty, Microsoft Certified: Azure AI Engineer Associate, or Certified Analytics Professional (CAP).
Additional InformationWork Environment 
