Chief Data Officer

Chenega Corporation
Wright-Patterson Air Force Base, OH, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Big Data Collaborative Software Data Architecture Data Integration Data Mining Data Structures Decision Support Systems Machine Learning Unstructured Data Generative AI SC Clearance
+1 more
Data Analytics

Job description

The Chief Data Officer shall provide advanced technical support to the AFRL/RA organization, focusing on the development and implementation of data-driven solutions to enhance research and engineering outcomes. This role supports the Chief Data Officer and AI leadership in designing and implementing digital engineering infrastructure, leveraging artificial intelligence (AI), machine learning (ML), and data science methodologies to transform large volumes of experimental, computational, and historical research data into actionable insights. The position plays a critical role in modernizing how hypersonic test and technical report data is accessed, structured, analyzed, and utilized-enabling improved research efficiency and innovation across AFRL initiatives., * Support the AFRL/RA team in the collection, storage, management, and retrieval of experimental and computational research data.

  • Develop and implement data-driven solutions to enhance research and engineering outcomes
  • Support the Chief Data Officer and AI leadership
  • Design and implement digital engineering infrastructure, leveraging artificial intelligence (AI), machine learning (ML), and data science methodologies to transform large volumes of experimental, computational, and historical research data into actionable insights
  • Assist in implementing and advancing digital engineering infrastructure aligned with government reference architectures.
  • Apply machine learning and AI-powered data mining techniques to:
  • Identify statistical trends within existing datasets
  • Detect gaps in available data (data paucity)
  • Improve the effectiveness of future experimental and computational efforts
  • Collaborate with AFRL/RA AI leadership to design and develop AI agents capable of:
  • Automating extraction of structured data from unstructured historical data packages
  • Utilizing metadata and technical reports to prioritize relevant information for end users
  • Develop and maintain scalable data structures and workflows that enable seamless:
  • Data integration
  • Analysis
  • Storage and retrieval across multiple platforms
  • Integrate heterogeneous datasets from multiple sources into unified analytical frameworks and modeling environments.
  • Support the creation of digital collaboration tools to:
  • Eliminate data silos
  • Enhance accessibility of structured research data
  • Provide streamlined user interfaces for data interaction
  • Enable transformation of fragmented information into structured, accessible, and analysis-ready datasets.
  • Contribute to model development and data-driven decision support tools for research stakeholders.
  • Other duties as assigned

Requirements

  • Master of Arts (MA)/Master of Science (MS) in Science; Engineering, Mathematics, or Statistics
  • Minimum ten (10) years in data science / OR A-type work
  • Minimum five (5) experience in designing AI/ML solutions, building data architectures, and creating automation (AI agents)
  • Minimum five (5) years working with large-scale or complex datasets
  • Minimum five (5) years supporting DoD research programs
  • Possess and maintain an Active Secret Clearance

Knowledge, Skills and Abilities

  • Knowledge of machine learning, artificial intelligence, and data science techniques
  • Ability to design and implement data architectures and workflows aligned with enterprise/government standards
  • Proficiency in handling structured and unstructured data, including data extraction and transformation
  • Skilled in integrating heterogeneous data sources into unified systems
  • Ability to develop and support AI-driven automation tools (e.g., data extraction agents)
  • Possess analytical and problem-solving skills applied to complex research datasets
  • Possess effective collaboration skills across technical, engineering, and research stakeholders
  • Possess excellent written and verbal communication skills for technical audiences
  • Ability to translate complex data into meaningful insights for decision-makers
  • Demonstrated technical communication skills, including preparation of briefings, technical reports, research papers, and publications.
  • Experience with high-speed flight vehicle technologies, hypersonics, or advanced aerospace systems Preferred
  • Experience with digital engineering concepts and frameworks Preferred
  • Experience working with large, complex, and diverse datasets Preferred
  • Experience in AI/ML model development, training, or deployment Preferred
  • Familiarity with generative AI tools and data-driven infrastructure development Preferred

Physical Demands (The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.)

  • The employee will need to be able to perform facility inspections.
  • While performing the duties of this Job, the employee is regularly required to sit and talk or hear. The employee may use repeated motions that include the arms, wrists, hands and/or fingers. The employee is occasionally required to walk, stand, climb, balance, stoop, kneel, crouch, or crawl. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on clearancejobs.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:12 min

Navigating technical clarity as a global black belt

Chris Heilmann +2 · LIVE

2:31 min

Data mining literary works for language patterns

Jen Looper Jen Looper · Europe 2026 Virtual

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

4:25 min

Analyzing web accessibility data at scale

Karl Groves Karl Groves · LIVE

2:10 min

Why organizations combine big data and machine learning

Ayon Roy · LIVE

Videos

See all

Related articles

See all