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Bayesian Phd 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 ...

Data Scientist III

Charlottesville, VA · On-site

$98K - $171K/yr

Typically requires a bachelor's degree, master's degree or PhD in data science, applied mathematics ... Familiarity with Kalman filtering, nonlinear filtering, Bayesian estimation, probabilistic data ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $220K/yr

... or PhD preferred * 5+ years of experience building and deploying production ML systems, with a ... Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $220K/yr

... or PhD preferred * 5+ years of experience building and deploying production ML systems, with a ... Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal ...

Data Scientist

Ashburn, VA · Hybrid

$83K - $139K/yr

... PhD/Doctorate and 0-3 years * Experience in developing machine learning models and applying ... Bayesian Networks, etc. * Experience with pattern recognition and extraction, automated ...

PhD in Industrial and Organizational Psychology, Organizational Behavior, or other technical or ... or Bayesian modeling * Experience working in cross-functional teams to push enterprise-level ...

Data Scientist

Ashburn, VA · On-site

$83K - $139K/yr

... PhD/Doctorate and 0-3 years * Experience in developing machine learning models and applying ... Bayesian Networks, etc. * Experience with pattern recognition and extraction, automated ...

PhD in Industrial and Organizational Psychology, Organizational Behavior, or other technical or ... or Bayesian modeling * Experience working in cross-functional teams to push enterprise-level ...

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Showing results 1-20

Bayesian Phd information

What are some common challenges faced by a Bayesian PhD researcher during collaborative projects?

Bayesian PhD researchers often collaborate with interdisciplinary teams, which can present challenges such as communicating complex statistical concepts to non-specialists and integrating Bayesian methods with other analytical frameworks. Balancing the depth of theoretical work with practical problem-solving, managing computational demands, and aligning project goals with collaborators' expectations are also common hurdles. Successful collaboration typically requires strong communication skills, adaptability, and a willingness to bridge methodological gaps between disciplines.

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

To thrive as a Bayesian PhD, you need advanced knowledge of probability theory, statistical inference, and mathematics, typically supported by a doctoral degree in statistics, mathematics, or a related field. Proficiency with statistical programming languages like R, Python, and specialized Bayesian tools such as Stan or BUGS is essential. Strong critical thinking, problem-solving, and clear communication skills help in articulating complex analyses and collaborating across disciplines. These capabilities are crucial for developing rigorous models, conducting impactful research, and translating statistical insights into actionable solutions.

What is the difference between Bayesian Phd vs Data Scientist?

AspectBayesian PhdData Scientist
Required CredentialsPhD in Statistics, Mathematics, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch-focused, academic or specialized industry rolesBusiness-focused, tech companies, or consulting firms
Industry UsageAcademic research, advanced analytics, specialized modelingData analysis, machine learning, business insights
Common Search/ComparisonYesYes

While a Bayesian PhD specializes in advanced statistical modeling and research, a Data Scientist applies data analysis and machine learning techniques in practical business contexts. Both roles require strong analytical skills, but the Bayesian PhD typically focuses on theoretical development, whereas the Data Scientist emphasizes application and implementation.

What is a Bayesian PhD?

A Bayesian PhD typically refers to an individual who has completed a doctoral program with a focus on Bayesian statistics or Bayesian methods in their research. Bayesian statistics is a branch of statistics that uses probability distributions to represent uncertainty about unknowns, updating beliefs as new data becomes available. Students in this field learn to develop and apply Bayesian models to a wide range of problems in science, engineering, and social sciences. A PhD program with a Bayesian focus often involves advanced coursework in probability theory, statistical inference, and computational methods, as well as original research using Bayesian approaches.
What cities in Virginia are hiring for Bayesian Phd jobs? Cities in Virginia with the most Bayesian Phd job openings:
Infographic showing various Bayesian Phd job openings in Virginia as of June 2026, with employment types broken down into 59% Full Time, 22% Part Time, and 19% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.
Data Scientist III

Data Scientist III

General Atomics

Charlottesville, VA • On-site

$98K - $171K/yr

Full-time

Posted 11 days ago


General Atomics rating

8.9

Company rating: 8.9 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

5th of 60 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

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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