Senior Computer Scientist

Booz Allen Hamilton

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: Aurora, CO
Salary: $99,000–$225,000 / yr
Posted: 23 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $182k

This role $162k

$84k most similar roles pay here $240k

This role pays less than 55% of similar roles. Most pay $151,475–$211,750 — the shaded band above. At the midpoint, this role pays about $162k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

About Booz Allen Hamilton

Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting

Booz Allen Hamilton currently has 802 open roles on FindRole.

Listed pay typically runs $86,800–$198,000 across 783 roles with salary data.

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At a glance

TL;DR · Senior Computer Scientist

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As a Computer Scientist, Senior on the national security team, you will serve as an advanced data scientist and researcher focused on strategic intelligence. You will lead complex data exploration and analytics projects while evaluating AI methodologies to mitigate risks and improve government efficiency. Your daily responsibilities include developing testing libraries using object-oriented and functional programming, managing CI/CD pipelines for machine learning validation, and building systems to evaluate the performance of LLMs or agentic AI. The role requires expertise in mathematics, statistics, information science, data mining, and data engineering. You will translate complex technical findings into visual and written narratives for non-technical leadership. Essential skills include experience with testing, evaluation, verification, and validation (TEVV) procedures within classified networks to solve critical problems regarding the reliability and fairness of advanced analytics systems.

Skills

Machine Learning Artificial Intelligence LLMs Agentic AI CI/CD Data Science Statistics Data Engineering Data Warehousing Data Mining Probability Modeling Object-Oriented Programming Functional Programming TEVV IoT Information Science

What you'll do

Evaluate AI methodologies and risk mitigation strategies to impact strategic intelligence.
Develop and execute testing, evaluation, verification, and validation (TEVV) procedures for AI systems.
Build modular and scalable testing libraries using object-oriented and functional programming.
Manage CI/CD pipelines specifically for the validation of AI and machine learning models.
Evaluate the performance, robustness, and fairness of advanced analytics including LLMs and agentic AI.
Translate complex technical findings into visual and written narratives for non-technical leadership.
Conduct data exploration and analysis to provide actionable results for Department of Defense clients.

What we're looking for

Active TS/SCI clearance and willingness to take a polygraph exam.
Bachelor’s degree and 8+ years of experience with scientific techniques such as mathematics, statistics, AI, machine learning, or data engineering.
12+ years of experience with scientific techniques in lieu of a bachelor's degree.
8+ years of experience correlating complex technical findings into graphical, written, visual, and verbal narrative products.
5+ years of experience with object-oriented and functional programming to build modular and scalable testing libraries.
Experience with CI/CD pipelines, including AI or ML validation.
Experience building and evaluating outputs and performance of advanced analytics, including LLMs or agentic AI.
Experience working on classified networks in support of DoD or IC clients.
Experience reviewing technical documentation for compliance with applicable standards (preferred).
Experience developing and executing TEVV procedures (preferred).
Experience evaluating AI system performance, robustness, and fairness (preferred).