Job SummaryAre 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
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; nine or more years of experience with a bachelor's degree, seven or more years of experience with a master's degree, or four 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
