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Bayesian Jobs in Virginia (NOW HIRING)

Data Scientist III

Charlottesville, VA · On-site

$98K - $171K/yr

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 ...

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 ...

Implement uncertainty quantification techniques, such as ensembling and Bayesian methods, to ensure robust and reliable predictions in nuclear systems. * Optimize nuclear engineering processes using ...

Apply causal inference, Bayesian modeling, survival analysis, and simulation to solve high-stakes business problems. * Translate ambiguity to impact: Frame undefined problems with entrepreneurial ...

Apply causal inference, Bayesian modeling, survival analysis, and simulation to solve high-stakes business problems. * Translate ambiguity to impact: Frame undefined problems with entrepreneurial ...

Senior Data Scientist

Springfield, VA · On-site

$117 - $195/hr

Bayesian Modeling * Data Processing * Demand forecasting * Data Management * Data Quality * Descriptive Analytics * D3.js * Atlassian Confluence * Atlassian Jira * 3D processing * 3D Mesh * BRep ...

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Showing results 1-20

Bayesian information

See Virginia salary details

$145.4K

$155.6K

$166.8K

How much do bayesian jobs pay per year?

As of Aug 10, 2026, the average yearly pay for bayesian in Virginia is $155,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $150,742.00 and $160,467.00 per year, depending on experience, location, and employer.

What are the typical projects or challenges faced in a Bayesian role?

In a Bayesian role, you’ll often work on projects involving probabilistic modeling, uncertainty quantification, and predictive analytics for real-world decision-making. Common challenges include structuring prior distributions, ensuring computational efficiency for complex models, and clearly explaining Bayesian results to non-technical stakeholders. You might collaborate closely with data engineers, domain experts, and business analysts to refine models and translate findings into actionable recommendations. This role offers the opportunity to tackle diverse analytical problems across industries like healthcare, finance, or tech, supporting ongoing professional growth and learning.

What is a Bayesian?

A Bayesian job typically involves applying Bayesian statistics, probabilistic modeling, and inference techniques to analyze data and make decisions under uncertainty. Professionals in this field use Bayes' theorem to update beliefs based on new evidence, often working in areas like machine learning, finance, healthcare, and research. Common roles include Bayesian statisticians, data scientists, and researchers who build probabilistic models to improve predictions and decision-making.

What jobs use Bayesian statistics?

Jobs that use Bayesian statistics include data scientists, statisticians, machine learning engineers, and quantitative analysts. These roles often involve developing probabilistic models, updating beliefs with new data, and using tools like R or Python for analysis. Bayesian methods are common in fields such as finance, healthcare, and research for decision-making and predictive modeling.

What are the key skills and qualifications needed to thrive in a Bayesian role, and why are they important?

To thrive as a Bayesian (typically a Bayesian Data Scientist or Statistician), you need a strong background in probability theory, statistical modeling, and mathematics, often with an advanced degree in statistics, data science, or a related quantitative field. Experience with programming languages such as Python or R, Bayesian analysis libraries (e.g., Stan, PyMC), and familiarity with statistical software are commonly required. Analytical thinking, collaborative teamwork, and the ability to communicate complex results clearly are valuable soft skills in this role. These abilities are essential for designing robust models, interpreting data accurately, and delivering actionable insights to interdisciplinary teams.

What are the most commonly searched types of Bayesian jobs in Virginia? The most popular types of Bayesian jobs in Virginia are:
Infographic showing various Bayesian job openings in Virginia as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 3% Hybrid, and 34% Remote job distribution, with an average salary of $155,605 per year, or $74.8 per hour.

Data Scientist III

General Atomics

Charlottesville, VA • On-site

$98K - $171K/yr

Full-time

Re-posted 17 days ago


General Atomics rating

9.0

Company rating: 9.0 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

11th of 72 rated aerospace companies


Job description

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:
  • 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

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About General Atomics

Sourced by ZipRecruiter

General Atomics (GA), and its affiliated companies, is one of the world's leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.

Industry

Space research administration

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1955