Data Scientist
Two Six Technologies
| Company | Two Six Technologies |
| Category | Data & Analytics |
| Location | Arlington |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 9 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
At Two Six Technologies, we build, deploy, and implement innovative products that solve the world’s most complex challenges today. Through unrivaled collaboration and unwavering trust, we push the boundaries of what’s possible to empower our team and support our customers in building a safer global future. We’re looking for an experienced Data Scientist or Senior Data Scientist to join one of our cross-functional product development teams here at Two Six Technologies. Our teams are building capabilities to identify, plan, and deliver effects in the information operations space, and aim to provide a complete end-to-end solution to customers wishing to detect, analyze, and respond to events in real time. We combine signal-rich proprietary data, novel AI-powered technology, and world-class expertise to deliver valuable insights to our US government and Fortune 50 clients.
We’re seeking a curious and passionate Data Scientist who will help our customers discover the information hidden in vast amounts of data to sense, make sense, and act in the Information Environment. In this role, you will work autonomously to find creative solutions and tackle challenging problems with cutting-edge technology, with a current focus on Agentic AI. The role is a great fit if you’re motivated by autonomy, innovation, and mission-focused data problems in uncharted territory to advance missions of national security.
As a part of the Data Science team you’ll have opportunities to work on projects that expand your skills, learn from peer mentors, and iterate internal research and development. We regularly experiment with a range of data science techniques to build tools and produce insights. Our team works with agentic and generative AI, machine learning, network analysis, sampling methodologies, multi-language NLP, data visualization, and more.
Responsibilities
Work with our product and customer support teams to turn abstract customer needs into concrete data science and/or engineering problems
Experiment with and evaluate potential solutions to develop high quality prototypes
Work with our engineering team to turn prototypes into scalable production-level software
Work on agentic systems – designing prototypes, adding tools, evaluating effectiveness
Be responsible for projects that span statistical and mathematical reasoning, business communications and leadership, and software development
Contribute to the product roadmap both near-term tactical and longer-term strategic levels
Experiment with a range of data science techniques to produce insight, including machine learning, deep learning, network analysis, sampling methodologies, text analytics in multiple languages and data visualization
Design and execute experiments to evaluate the integrity of our data sampling and data collection strategies
Work on ad-hoc analyses or build prototype tools to support our subject matter expert and customer support teams
Participate in strategic discussions about the direction data science should be taking the company
Here are some of the skills and experience that will help you thrive in this role:
Background
Strong quantitative background with Bachelor’s degree in Physics, Computer Science, Math, Statistics, Economics, Engineering, or similar field. Higher degrees preferred
You have 3+ years experience in a Data Science role (or 1+ with a PhD), including 2+ years experience with Python programming language (Intermediate-level or higher)
Technical
Experience with agentic and generative AI. Examples include
Building agentic systems
Building tools for agentic systems
Evaluating agentic systems and/or generative AI solutions
LangChain and/or LangGraph frameworks
Model Context Protocol and Agent2Agent Protocol
Prompt engineering
Leveraging LLMs within analytical pipelines
Training or fine-tuning LLMs
Experience with Machine Learning, including