Today
Top Secret/SCI
Senior Level Career (10+ yrs experience)
CI Polygraph
IT - Data Science
Tampa, FL (On-Site/Office)
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.
Requirements:
• 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.
Requirements:
• 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.
group id: 91115602
