Research Statistician - Tracking and Estimation Theory

General Atomics Intelligence

Charlottesville (VA)

On-site

USD 98,000 - 171,000

Full time

14 days+

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Job summary

GA-Intelligence in Charlottesville seeks a Statistics PhD to develop tracking algorithms that process data from heterogeneous sensors, fuse tracks across domains, and enable time-critical intelligence decisions.

You will apply Bayesian inference, state-space modeling, and Monte Carlo methods to multi-target tracking challenges that combine mathematical rigor with operational constraints. You will work with engineers to deploy algorithms at scale and stay engaged with the research community.

Qualifications

PhD in statistics or related quantitative field with Bayesian focus.
Experience with state-space models and sequential estimation.
Ability to communicate complex statistics to technical and non-technical audiences.
Proven track record in research publications or conference presentations.
Ability to obtain and maintain a DoD security clearance.

Responsibilities

Research and develop state-of-the-art tracking algorithms.
Validate performance with Monte Carlo simulations on real data.
Collaborate with analysts and engineers to deploy production-ready algorithms.
Publish internal research and present findings to diverse audiences.
Mentor junior researchers and shape future research directions.

Skills

Bayesian inference

State-space modeling

Monte Carlo methods

Python

MATLAB

C++

Java

Data fusion

Multi-target tracking

Education

PhD in Statistics

Dissertation on Bayesian inference

Strong foundations in probability & statistics

Tools

Python

MATLAB

C++

Java

Job description

Job Summary

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

Job Summary

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: