Data Scientist (AI/ML)

TechniPros, LLC
Rockville, MD, United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$100,000.0 - $120,000.0
Working hours
Regular working hours

Tech stack

Agile Methodology Artificial Intelligence Data Analysis Systems Engineering Computer Vision Cloud Computing Cloud Engineering Data Files Machine Learning Microsoft Office Scrum Methodology Software Architecture
+4 more
Systems Development Life Cycle Software Engineering Model Validation Machine Learning Operations

Job description

Provide technical expertise supporting AI/ML software acquisition programs. Perform data collection, analysis, and reporting to improve transparency and explainability of AI/ML systems. Support development, scaling, validation, and evaluation of machine learning models. Assist Government customers in managing AI/ML analytics programs and initiatives. Evaluate software architectures and provide recommendations for future cloud-based systems.

Requirements

  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Data Science
  • Software Architecture
  • Systems Engineering
  • Cloud Computing Architecture
  • Model Evaluation & Validation
  • Responsible AI
  • Training Dataset Generation
  • Ontologies
  • Computer Vision
  • AI/ML Analytics
  • Data Analysis
  • Technical Documentation
  • Technical Roadmaps
  • Acquisition Strategy Support
  • Agile Methodologies
  • Scrum
  • SAFe
  • Agile Metrics
  • Risk Analysis
  • Software Development Lifecycle (SDLC)
  • Microsoft Office Suite

Soft Skills

  • Excellent analytical and problem-solving abilities
  • Strong critical thinking skills
  • High level of initiative and ownership
  • Excellent written and verbal communication skills
  • Ability to work effectively in high-tempo environments
  • Strong collaboration and teamwork skills
  • Ability to communicate technical concepts to Government stakeholders

Preferred Skills

  • Computer Vision
  • Mission-focused AI/ML analytics
  • Technical roadmap development
  • Government acquisition support
  • Cloud-native software architectures
  • Explainable AI (XAI)
  • AI governance and responsible AI frameworks

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