Data Scientist

We are seeking a Data Scientist to support a high-visibility Air Force capabilities marketing and demonstration effort. This role will focus on developing, analyzing, and integrating data models that support operational readiness, capability assessment, and decision-making across a large platform that connects to multiple applications.

The ideal candidate is technically strong in Python, SQL, and machine learning, able to work independently from assigned tasks, and comfortable presenting insights to both technical stakeholders and Air Force clients. This team values curiosity, collaboration, and strong communication as much as technical skill.

Key Responsibilities

Analyze and model structured and unstructured data using Python-based analytics, including exploratory data analysis (EDA) and anomaly detection.

Design, develop, and evaluate supervised and unsupervised machine learning models to assess system performance, readiness metrics, and operational decision support.

Build and manage data models, taxonomies, and schemas that enable cross-system interoperability and integration across a large, evolving platform.

Integrate data across systems using APIs and SDKs, supporting data pipelines, model workflows, and downstream applications.

Contribute to AI-enabled solutions, including basic understanding of LLMs, agent-based workflows, and NLP, while applying good judgment where AI-generated outputs require validation.

Collaborate closely with researchers, full-stack developers, and ML engineers to support evolving analytical and agentic workflows.

Manage and maintain databases, ensuring data integrity, normalization, and usability in constrained or mission-critical environments.

Develop and communicate clear insights, dashboards, and metrics that answer questions such as "What decisions can we make today?" and "What are we ready for now?"

Present findings professionally and confidently to internal teams and external Air Force stakeholders.

Bachelor's degree in Data Science, Computer Science, Information Science, Engineering, or a related field.

5+ years of experience in Python-based data analysis, including EDA and statistical modeling (or equivalent demonstrated capability for more junior candidates).

Experience working with SQL and relational databases.

Experience integrating and working across multiple data sources using APIs or SDKs.

Understanding of machine learning concepts, including supervised and unsupervised approaches.

Ability to work independently, take ownership of tasks, and operate with minimal oversight.

Strong written and verbal communication skills, with the ability to explain complex data concepts to non-technical audiences.

Ability to obtain a U.S. security clearance (active clearance is a strong plus). Active Top Secret or TS/SCI clearance.

Experience with cloud platforms (AWS preferred).

Experience with application development (full-stack or backend exposure is a strong plus).

Familiarity with NLP, agent-based systems, or agentic AI workflows.

Experience with geospatial or ISR-related data, including formats such as GeoJSON or WKT.

Knowledge of semantic web or data modeling technologies (RDF, OWL, JSON-LD, SKOS, SHACL).

Experience with event-driven architectures, streaming data, or data governance frameworks.

Background in research-heavy environments, deep analytical work, or applied R&D teams.

Familiarity with Agile tools such as JIRA or Confluence.

$90,000 - $135,000 per year annual salary.

Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role may include healthcare insurance offerings and paid leave as provided by applicable law.