TELECOMMUTE Data Scientist

Propertyvalue Quantum Technologies Llc

Chantilly, VA, United States

about 1 month ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience required

0 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Agile Methodology Artificial Intelligence Computer Vision Cloud Computing Monitoring of Systems Machine Learning Scrum Methodology Software Architecture Model Validation Technical Debt Machine Learning Operations

Job description

Provide data collection and analysis to enable transparency and explainability of AI/ML systems.
Provide technical and engineering support to the Government customer to manage machine learning analytics programs; apply knowledge and experience to develop and scale AI/ML models in multiple phenomenologies.
Provide software architecture and other technical expertise to support the planning of future systems and architectures, and oversight of development contractors.
Apply systems analysis and design methodology assessments to identify technical debt, architectural runway and efficiency trade-offs against current and proposed/desired cloud-based software system design.
Develop briefings and documentation material to illustrate features, capabilities and mission use cases for the computer vision tool portfolio, including developing technical roadmaps and the acquisition strategies/documentation to implement them.
Facilitate technical and programmatic interchanges; identify and resolve issues; and provide engineering and technical advice to the customer to achieve innovative capabilities for automated machine learning analytics.
You will work side-by-side with the other LANDMARK AOS staff comprised of world class System Engineers, Acquisition Engineers and Domain Experts to lead the customer in acquiring modern processing applications.

Requirements

Bachelors and two (2) years or more experience; Masters and 0 years related experience.
Active Top Secret Clearance with Polygraph.
Strong engineering background with knowledge of software architectures and machine learning approaches.
Experience with ontologies, training dataset generation, model evaluation and validation, and responsible AI practices.
Domain knowledge in Agile software development practices (Scrum, SAFe) and cloud computing architectures with experience monitoring software development progress via agile metrics, identifying risks, discrepancies, and performance issues.
Demonstrated high level of initiative, creative problem-solving, and critical thinking.
Demonstrated capability and success working in team environments.
Strong oral and written communications ability on significant technical matters often requiring coordination within a high-tempo environment.
Good working knowledge of MS Office applications.