Senior Data Scientist; TS/SCI CI Poly
Listed on 2026-07-10
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist, Data Engineering
When you join DeNOVO, you’re not just starting a job, you’re advancing a career within a community that values and supports you.
Position InformationPosition: Senior Data Scientist (TS/SCI with CI Poly Required)
Location: Aurora, CO
Job : CORP-DS3-001
Openings: 0
Clearance: TS/SCI with CI Polygraph
Role OverviewDeNOVO Solutions is seeking a Senior Data Scientist to help develop, refine, and strengthen our data science and mission‑focused technical capabilities. This is a unique opportunity for a senior‑level data scientist with a strong background in applied machine learning, data engineering, software development, secure deployment environments, and technical leadership. The ideal candidate will be comfortable working across research, development, architecture, deployment, and stakeholder engagement while helping shape practical AI/ML solutions for emerging mission needs.
WhyYou’ll Love This Role
- Help develop and refine DeNOVO’s broader data science capability
- Work closely with DeNOVO’s CEO in a highly visible role focused on capability growth and technical direction
- Apply advanced data science, machine learning, data engineering, and software development experience to emerging mission needs
- Help shape practical AI/ML solutions that support mission‑focused opportunities
- Work in a hands‑on role that blends research, solution design, implementation, deployment, and stakeholder collaboration
- Help develop and refine DeNOVO’s data science capability
- Research, build, evaluate, and deploy machine learning and AI‑enabled applications
- Design and implement data science solutions that align with user needs, mission goals, and technical objectives
- Communicate with technical and non‑technical stakeholders to understand requirements, data landscapes, and solution goals
- Provide technical recommendations to ensure data science and AI/ML solutions are practical, scalable, and aligned to stakeholder needs
- Develop and support machine learning, generative AI, and LLM‑based applications where applicable
- Support semantic search, summarization, text extraction, classification, embedding analysis, and natural language processing use cases
- Build scalable data pipelines and support data engineering workflows
- Develop backend services, APIs, microservices, and data‑driven applications
- Support deployment of software and data science applications in commercial cloud and secure environments
- Use containerization and orchestration technologies to package, deploy, and manage software components
- Support MLOps, Dev Ops, and Git Ops practices to improve repeatability, deployment efficiency, and lifecycle management
- Develop visualizations, dashboards, and analytical tools to help communicate insights and recommendations
- Collaborate with leadership, engineers, and stakeholders to identify opportunities for data science, automation, and AI/ML capability growth
- Provide technical leadership, mentoring, and guidance to other technical contributors as needed
- Create documentation, technical recommendations, and capability‑development materials to support long‑term growth
- Senior‑level experience in data science, data engineering, machine learning, and software development
- Experience researching, building, evaluating, and deploying machine learning and AI‑enabled applications
- Strong background with applied machine learning, including supervised and unsupervised learning approaches
- Experience with generative AI, large language models, RAG, semantic search, summarization, text extraction, and NLP‑related use cases
- Experience building scalable data pipelines and supporting data engineering workflows
- Experience developing APIs, microservices, backend services, and data‑driven applications
- Experience deploying software or data science applications in commercial cloud and secure environments
- Experience with containerization, orchestration, and modern deployment practices
- Familiarity with MLOps, Dev Ops, Git Ops, Agile/Scrum, and modern software development methodologies
- Strong communication skills with the ability to work with technical and non‑technical stakeholders
- Ability to provide technical leadership, mentorship, and solution…
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