Location
In office (Chantilly)
Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 11, 2026. XMSTART scores B on the Alion truth index.
Overview
Company
Impact
Profile match
XMSTART is an employee-owned professional services and defense contracting firm specializing in systems engineering, data analytics, IT management, and mission-critical support. Headquartered in Fairfax, Virginia, the company delivers specialized technical and program management expertise to various national security and defense agencies. Through a multidisciplinary team of engineers and technical professionals, the enterprise provides strategic consulting, acquisition support, and complex technical solutions for government operations.
XMSTART is looking to add experienced and strategic full-time Data Scientists to our teams in Chantilly, VA and Aurora, CO. These positions are 100% onsite.
The Data Scientist applies data analysis, modeling, and AI/ML techniques to help extract insight from data, supporting decision-making, and improve mission performance and business processes.
Responsibilities may include but are not limited to:
- Preparing, cleaning, and exploring structed and unstructured data
- Developing analytic approaches, features, and models to address mission needs
- Evaluating model performance and supporting validation or testing activities
- Creating visualizations, summaries, and reports to communicate findings
- Assisting with data quality assessment, data management, and documentation
- Collaborating with stakeholders to refine requirements and support decision-making
Requirements
- An active TS/SCI with Poly
- Junior - 0 to 5 years of Experience, Intermediate - 5 to 10 years of Experience, Senior - 10+ years of experience
- Experience in data science, analytics, statistics, AI/ML, or a related field
- Ability to analyze data and communicate findings clearly
- Familiarity with data preparation, modeling, evaluation, and visualization practices
- Strong problem-solving skills and attention to data quality
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