Research Statistician - Tracking and Estimation Theory
General Atomics —Charlottesville, VA
- $98,100 - $171,398 a year
- Full-time
- Computer Science
- 3 years
- Java
- Relocation assistance
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- Online Application
- Background check
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- Health insurance
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Postdoctoral Research Associate, Physics-Aware Deep Learning
University of Virginia —Charlottesville, VA
- $65,000 - $70,000 a year
- Online Application
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Research Statistician - Tracking and Estimation Theory

General Atomics -
Charlottesville, VA

Apply Now

Job Details

Full-time
$98,100 - $171,398 a year

Benefits

Relocation assistance

Qualifications

Computational modeling

Full Job Description

Are you a statistician who wants to see your Bayesian models protect national security?

GA-Intelligence is seeking a Statistics PhD to develop tracking algorithms that process data from heterogeneous sensors, fuse tracks across domains, and enable time-critical intelligence decisions. You'll apply statistical inference, state-space modeling, and Monte Carlo methods to multi-target tracking challenges that combine mathematical rigor with operational constraints.

Your work will span algorithm research, operational analysis, and production deployment—from deriving novel filters to validating performance on classified sensor data to partnering with engineers who implement your algorithms at scale.

DUTIES AND RESPONSIBILITIES:

Algorithm Research and Development:

Guide the development of state-of-the-art tracking algorithms from existing tracking literature, ensuring technical correctness.
Develop statistical approaches to data association in multi-target, multi-sensor environments
Derive probabilistic models for target behavior and sensor measurement processes
Prototype algorithms in Python, MATLAB, or R and validate performance through Monte Carlo simulation
Apply modern statistical and computational methods to emerging tracking challenges

Operational Impact:

Collaborate with intelligence analysts to understand tracking requirements and operational constraints
Analyze tracking performance on real-world sensor data from classified systems
Quantify and communicate uncertainty, assumptions, and limitations to support operational decision-making
Translate operational gaps into tractable statistical problems
Partner with software engineers to transition algorithms from prototype to production

Research Leadership:

Publish internal research on tracking advances and algorithmic innovations
Present findings to technical staff, program managers, and government decision-makers, as well as external conferences
Contribute to proposal development and help shape future research directions
Mentor junior team members and future hires
Stay current with tracking research literature and evaluate applicability to operational problems

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

Job Qualifications

Typically requires a bachelor's degree, master's degree or PhD in data science, applied mathematics, statistics, computer science, or related technical/quantitative discipline from an accredited institution and progressive data science experience as follows; five or more years of experience with a bachelor's degree, three or more years of experience with a master's degree, or one or more years with a PhD. May substitute equivalent experience in lieu of education.
Strong preference for PhD in Statistics, Biostatistics, or closely related quantitative field
Dissertation research in Bayesian inference, state-space modeling, sequential estimation, or time series analysis
Strong foundations in statistical inference, probability theory, statistical modeling, and Bayesian methods
Deep understanding of state-space models, Kalman filtering, and sequential Monte Carlo methods
Expertise in stochastic processes and time series analysis
Proficiency in Python, MATLAB, R, or similar scientific computing languages
Experience implementing statistical algorithms and conducting simulation studies
Strong analytical and problem-solving abilities
Ability to communicate complex statistical concepts clearly to technical and non-technical audiences
Curiosity about operational applications and mission context
Collaborative mindset—works well with software engineers, intelligence analysts, and researchers
Ability to obtain and maintain a DoD security clearance is required.

Preferred Qualifications:

Domain Experience:

Familiarity with tracking, navigation, or multi-target systems
Experience with sensor fusion or data association problems
Knowledge of Extended Kalman Filters, Unscented Kalman Filters, particle filters, or IMM filters
Understanding of coordinate transformations and reference frames

Research Background:

Contributed to peer-reviewed publications, technical reports, or conference presentations
Experience with probabilistic programming frameworks
Dissertation work involving real-world sensor data or applied problems
Prior internships or collaborations with defense, aerospace, or robotics organizations
Experience writing technical proposals for government research projects
Experience leading technical projects or mentoring junior researchers

Technical Breadth:

Programming experience in one or more languages such as Python, C++, Java
High-performance computing or numerical optimization
Version control (Git) and collaborative development practices
Exposure to real-time systems or computational constraints

Why Join GA-Intelligence

Operational Impact: Your tracking algorithms will run in production systems supporting intelligence analysts and military personnel. Your work directly contributes to national security missions.

Technical Challenge: Multi-target tracking in adversarial environments with heterogeneous sensors is an unsolved research problem. You'll tackle cutting-edge algorithmic challenges that combine statistical rigor with operational constraints.

Collaborative Environment: Work alongside tracking mathematicians, software engineers, intelligence analysts, and mission experts. We value diverse perspectives and believe the best solutions emerge from multidisciplinary collaboration. Our team is committed to advancing the state-of-the-art in tracking while maintaining a culture of innovation, integrity, and teamwork.

Research Opportunities: Continue publishing research, present at conferences, and contribute to the tracking research community while delivering operational capabilities.

Charlottesville Location:

Blue Ridge Mountains and Shenandoah National Park (30 minutes)
University town culture with intellectual community (University of Virginia)
Short average commute (no DC Beltway traffic)

Career Growth:

Build and lead tracking algorithm research team over time
Technical leadership opportunities
Shape strategic direction of tracking capabilities

Job Category

Engineering

Experience Level

Mid-Level (3-7 years)

Workstyle

Onsite

Full-Time/Part-Time

Full-Time Salary

Pay Range Low

98,100

Pay Range High

171,398

Travel Percentage Required

0% - 25%

Relocation Assistance Provided?

Yes

US Citizenship Required?

Yes

Clearance Required?

Desired

Clearance Level

Top Secret (current SCI access with CI Poly)

Search Jobs at | General Atomics and Affiliated Companies

Apply Now

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Research Statistician - Tracking and Estimation Theory

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