ClearanceJobs
AI/ML Data Scientist
SHC Federal is seeking a highly motivated AI/ML Data Scientist to support a high-impact federal program on a full-time onsite basis in the MacDill AFB, FL area. The ideal candidate will meet the following criteria: Master's degree in computer science, Machine Learning, Statistics, Mathematics, or related (or equivalent experience). 8+ years of industry experience in predictive modeling, data science, and analytics. Hands-on experience with Advana, Maven, or Databricks. Expertise in machine learning & deep learning algorithms, frameworks, and tools. Strong programming/software engineering skills with focus on AI models for logistics and decision support systems. Proven record of developing and integrating AI/ML models with large-scale data repositories. Experience supporting command-level decision support tools and logistical data systems. Familiarity with Cyber, Knowledge, and Information Management in military/operational environments. Ability to collaborate with cross-functional and command staff teams. Responsibilities: Develop and integrate AI/ML models (machine learning, deep learning) with Command Common Operating Picture data repositories. Deliver advanced analytics solutions with geographic visualizations, dashboards, and predictive/prescriptive analytics. Partner with stakeholders to align AI/ML workflows with Cyber, Knowledge, and Information Management processes. Build predictive models from large datasets for logistics objectives and decision-making. Design and implement data ingestion/transformation pipelines to connect with enterprise repositories. Ensure AI/ML models are built to enterprise standards, enabling efficient data sharing across joint enterprise systems. Build and manage data pipelines leveraging AWS infrastructure and modern development tools. Apply expertise in service-oriented architecture to deliver scalable, resilient solutions. Collaborate within an Agile team environment, contributing to sprint planning, reviews, and retrospectives. Embrace a culture of continuous learning, innovation, and calculated risk-taking to drive mission success.
SHC Federal is seeking a highly motivated AI/ML Data Scientist to support a high-impact federal program on a full-time onsite basis in the MacDill AFB, FL area. The ideal candidate will meet the following criteria: Master's degree in computer science, Machine Learning, Statistics, Mathematics, or related (or equivalent experience). 8+ years of industry experience in predictive modeling, data science, and analytics. Hands-on experience with Advana, Maven, or Databricks. Expertise in machine learning & deep learning algorithms, frameworks, and tools. Strong programming/software engineering skills with focus on AI models for logistics and decision support systems. Proven record of developing and integrating AI/ML models with large-scale data repositories. Experience supporting command-level decision support tools and logistical data systems. Familiarity with Cyber, Knowledge, and Information Management in military/operational environments. Ability to collaborate with cross-functional and command staff teams. Responsibilities: Develop and integrate AI/ML models (machine learning, deep learning) with Command Common Operating Picture data repositories. Deliver advanced analytics solutions with geographic visualizations, dashboards, and predictive/prescriptive analytics. Partner with stakeholders to align AI/ML workflows with Cyber, Knowledge, and Information Management processes. Build predictive models from large datasets for logistics objectives and decision-making. Design and implement data ingestion/transformation pipelines to connect with enterprise repositories. Ensure AI/ML models are built to enterprise standards, enabling efficient data sharing across joint enterprise systems. Build and manage data pipelines leveraging AWS infrastructure and modern development tools. Apply expertise in service-oriented architecture to deliver scalable, resilient solutions. Collaborate within an Agile team environment, contributing to sprint planning, reviews, and retrospectives. Embrace a culture of continuous learning, innovation, and calculated risk-taking to drive mission success.