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Bayesian Networks Jobs in Silver Spring, MD (NOW HIRING)

Peraton

Risk Analysis Engineer

Annapolis Junction, MD · On-site

$86K - $138K/yr

Experience with Bayesian networks or causal modeling * Knowledge of portfolio risk aggregation techniques Peraton Overview Peraton is a next-generation national security company that drives missions ...

Peraton

Risk Analysis Engineer

Annapolis Junction, MD · On-site

$86K - $138K/yr

Experience with Bayesian networks or causal modeling * Knowledge of portfolio risk aggregation techniques Peraton Overview Peraton is a next-generation national security company that drives missions ...

ManTech

Data Scientist

Ashburn, VA · Hybrid

... Bayesian Networks, etc. * Experience with pattern recognition and extraction, automated classification, and categorization and with entity resolution (e.g., record linking, named entity matching ...

ManTech International

Data Scientist

Ashburn, VA · On-site

... Bayesian Networks, etc. * Experience with pattern recognition and extraction, automated classification, and categorization and with entity resolution (e.g., record linking, named entity matching ...

Barrow Wise Consulting

AI Engineer

MD · On-site

$80K - $160K/yr

... as Bayesian, coordinate descent, gradient descent, and evolutionary * Utilizes big data computation and storage models to create prototypes and data sets * Develop Convolutional Neural Networks and ...

Digital Harbor Foundation

Research Scientist

Baltimore, MD · On-site +1

$120K - $150K/yr

... Networks, or AI-accelerated FEM modeling * Familiarity with uncertainty quantification methods (e.g., ensembles, Bayesian inference) and sensitivity analysis techniques (e.g., adjoint methods) in a ...

Digital Harbor Foundation

Research Scientist

Baltimore, MD · Remote

$120K - $150K/yr

... Networks, or AI-accelerated FEM modeling * Familiarity with uncertainty quantification methods (e.g., ensembles, Bayesian inference) and sensitivity analysis techniques (e.g., adjoint methods) in a ...

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Bayesian Networks information

What is the difference between Bayesian Networks vs Data Analysts?

AspectBayesian NetworksData Analysts
Required CredentialsStatistics, Data Science, Computer Science degrees; certifications in probabilistic modelingStatistics, Data Science, Business Analytics degrees; certifications in data analysis tools
Work EnvironmentResearch, modeling, and algorithm development in tech or research firmsData interpretation, reporting, and visualization across various industries
Industry UsageUsed for probabilistic reasoning, decision support, and machine learningUsed for data interpretation, reporting, and business insights

Bayesian Networks focus on probabilistic modeling and decision-making algorithms, often requiring advanced statistical knowledge. Data Analysts primarily interpret and visualize data to inform business decisions. While both roles involve data, Bayesian Networks are more technical and model-driven, whereas Data Analysts focus on data interpretation and reporting.

What are Bayesian Networks?

Bayesian Networks are probabilistic graphical models that represent a set of variables and their conditional dependencies using a directed acyclic graph. They are used to model uncertainty in complex systems by encoding relationships between variables and allowing for efficient inference and reasoning. These networks are widely applied in fields such as machine learning, diagnostics, decision support, and bioinformatics to help predict outcomes and understand causal relationships.

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

To thrive as a Bayesian Networks Specialist, you need a strong background in statistics, probability theory, and machine learning, often supported by a degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, and experience using specialized libraries like pgmpy or bnlearn, are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills set standout professionals apart in this role. These competencies are crucial for designing, implementing, and interpreting Bayesian models that inform critical decision-making in complex domains.

What are some common challenges faced by professionals working with Bayesian Networks in real-world projects?

Professionals working with Bayesian Networks often encounter challenges such as handling incomplete or noisy data, defining accurate conditional dependencies, and ensuring computational efficiency for large or complex networks. Collaboration with domain experts is crucial to correctly structure the network and validate assumptions. Additionally, integrating Bayesian models with existing data systems and effectively communicating probabilistic results to non-technical stakeholders are important aspects of the role.
What are popular job titles related to Bayesian Networks jobs in Silver Spring, MD? For Bayesian Networks jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Bayesian Networks jobs in Silver Spring, MD look for? The top searched job categories for Bayesian Networks jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Bayesian Networks jobs? Cities near Silver Spring, MD with the most Bayesian Networks job openings:
Bayesian Networks jobs near you
Risk Analysis Engineer

Risk Analysis Engineer

Peraton

Annapolis Junction, MD • On-site

$86K - $138K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Peraton rating

8.2

Company rating: 8.2 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

45th of 204 rated it services

Job description

Responsibilities
Peraton Labs is seeking a Risk Analysis Engineer to develop automated risk analysis capabilities including risk register management, risk identification from unstructured sources, Monte Carlo simulation, and cross-portfolio risk cascade modeling. Enables program offices to move from reactive risk management to proactive, data-driven risk intelligence.
Key Responsibilities
  • Build risk register management capabilities: creation, tracking, scoring, mitigation planning, and closure workflows
  • Develop automated risk identification from unstructured sources (meeting notes, emails, briefings) using NLP-extracted signals
  • Implement Monte Carlo simulation engines for schedule risk analysis (SRA) and cost risk analysis
  • Design risk scoring models that combine traditional likelihood/impact matrices with NLP-detected risk signals
  • Build risk interconnection mapping that models how risks cascade across programs within a portfolio
  • Develop risk trend analysis and burn-down tracking
  • Implement risk reporting and visualization data outputs (risk matrices, tornado diagrams, S-curves)
  • Collaborate with PM Domain Analysts to validate risk models against established frameworks

#px2026
Qualifications
Required Qualifications
  • 5+ years of experience with a Bachelor's degree, 3+ years with a Master's degree, or a PhD in Engineering, Mathematics, Statistics, or related field; Master's preferred
  • History of professional software engineering experience with quantitative analysis or risk modeling focus
  • Strong Python proficiency; experience with statistical computing (NumPy, SciPy, pandas)
  • Experience with Monte Carlo simulation and probabilistic modeling
  • Understanding of risk management frameworks and methodologies
  • Experience with data visualization for analytical outputs
  • Strong mathematical and statistical reasoning skills
  • US Citizenship with the ability to obtain/maintain a Secret clearance

Preferred Qualifications
  • Experience with defense program risk management (DoD Risk, Issue, and Opportunity Management Guide)
  • Familiarity with schedule risk analysis tools (Polaris, Primavera Risk Analysis)
  • Experience with Bayesian networks or causal modeling
  • Knowledge of portfolio risk aggregation techniques

Peraton Overview
Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.
Target Salary Range
$86,000 - $138,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
EEO
EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.

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About Peraton

Sourced by ZipRecruiter

At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017

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