Senior Data Scientist
Confirmed live in the last 24 hours
Two Six Technologies

501-1,000 employees

Develops cybersecurity and data science solutions for global safety
Company Overview
Two Six Technologies is a leader in the tech industry, known for its commitment to solving complex global challenges through private R&D and technical expertise in various fields such as cyber, information operations, and data science. The company fosters a culture of collaboration and trust, enabling its team to create impactful products that enhance global safety and are trusted by high-profile customers like DARPA and U.S. Cyber Command. With a focus on rapid development and real-world application, Two Six Technologies offers a dynamic work environment for those passionate about making a significant difference on a global scale.
Data & Analytics
AI & Machine Learning

Company Stage


Total Funding





Arlington, Virginia

Growth & Insights

6 month growth


1 year growth


2 year growth

Augusta, GA, USA
Experience Level
Desired Skills
Data Science
Operations Research
Data & Analytics
Finance & Banking
  • 10 years relevant experience with Bachelors in related field; or 8 years experience with Masters in related field; or 6 years experience with a Doctoral degree in a related field; or 12 years of relevant experience and an Associates may be considered for individuals with in-depth experience
  • Degree in an Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science, or related field of technical rigor
  • Ability/willingness to work full-time onsite in secure government workspaces
  • Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university
  • This position requires a TS/SCI with CI Poly and eligibility/willingness to obtain FS Poly
  • Devise strategies for extracting meaning and value from large datasets
  • Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge
  • Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in data holdings
  • Translate practical needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data
  • Effectively communicate complex technical information to non-technical audiences