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Probabilistic Modeling Jobs in Washington (NOW HIRING)

Peraton

Risk Analysis Engineer

Annapolis Junction, MD · On-site

$86K - $138K/yr

Experience with Monte Carlo simulation and probabilistic modeling * Understanding of risk management frameworks and methodologies * Experience with data visualization for analytical outputs * Strong ...

Peraton

Risk Analysis Engineer

Annapolis Junction, MD

$86K - $138K/yr

Experience with Monte Carlo simulation and probabilistic modeling * Understanding of risk management frameworks and methodologies * Experience with data visualization for analytical outputs * Strong ...

Peraton

Risk Analysis Engineer

Annapolis Junction, MD · On-site

$86K - $138K/yr

Experience with Monte Carlo simulation and probabilistic modeling * Understanding of risk management frameworks and methodologies * Experience with data visualization for analytical outputs * Strong ...

QxBranch

Data Scientist QxBranch

Washington, DC

Expertise in one or more of: natural language processing, probabilistic modeling, time series analysis, anomaly detection, deep learning, behavioral analysis, causal analysis * Strong data ...

QxBranch

Data Scientist QxBranch

Washington, DC · On-site

Expertise in one or more of: natural language processing, probabilistic modeling, time series analysis, anomaly detection, deep learning, behavioral analysis, causal analysis * Strong data ...

Guidehouse

Project Manager, PPRL

Bethesda, MD

$98K - $163K/yr

Develop and implement automated scoring and evaluation protocols using probabilistic modeling combined with strong statistical and analytical expertise. * Review and analyze the analytical outputs ...

QED Enterprises Inc

Data Scientist

Camp Springs, MD · On-site

$135K - $145K/yr

Expand on summary statistics using Tableau to run new and existing deterministic and probabilistic models addressing eligibility, risk, and complexity screening protocols. Interpret complex ...

Guidehouse

Project Manager, PPRL

Bethesda, MD · On-site

$98K - $163K/yr

Develop and implement automated scoring and evaluation protocols using probabilistic modeling combined with strong statistical and analytical expertise. * Review and analyze the analytical outputs ...

TechWish

Quantitative Risk Modeler

Vienna, VA · Hybrid

$55 - $71.25/hr

Advanced knowledge in probabilistic theory, game theory, dynamic systems theory and related disciplines. Strong understanding of database design, data mining, and data modeling concepts. Proven ...

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Probabilistic Modeling information

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

To thrive as a Probabilistic Modeler, you need a strong background in mathematics, statistics, and probability theory, often supported by a degree in applied mathematics, statistics, or a related field. Proficiency with programming languages like Python or R, and experience with statistical modeling tools and software such as TensorFlow or PyMC, are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help translate complex models into actionable insights. These skills are vital for designing accurate models, interpreting uncertainty, and supporting data-driven decisions across various industries.

What are some common challenges faced by professionals in probabilistic modeling roles, and how can they be managed?

Professionals in probabilistic modeling often encounter challenges such as working with incomplete or noisy data, choosing the right model complexity, and ensuring model interpretability for stakeholders. Managing these challenges involves strong statistical knowledge, regular collaboration with domain experts, and effective communication to translate complex results for non-technical team members. Staying up-to-date with the latest tools and methodologies, and participating in peer reviews, can also help maintain model accuracy and reliability.

What is probabilistic modeling?

Probabilistic modeling is a mathematical framework used to represent uncertain events or data by using probability distributions. Instead of giving a single outcome, it accounts for variability and randomness, allowing predictions and inferences even when information is incomplete or ambiguous. Probabilistic models are widely used in fields like statistics, machine learning, finance, and engineering to analyze data, make forecasts, and support decision-making under uncertainty.

What is the difference between Probabilistic Modeling vs Data Scientist?

AspectProbabilistic ModelingData Scientist
Required CredentialsDegree in statistics, mathematics, or related fields; knowledge of probability theoryDegree in computer science, statistics, or related fields; programming skills
Work EnvironmentResearch-focused, often in analytics or data science teamsCross-functional teams, including business, engineering, and analytics
Industry UsageUsed in analytics, finance, healthcare, and research for modeling uncertaintyApplied across industries for data analysis, predictive modeling, and decision-making

Probabilistic Modeling focuses on developing models based on probability theory to understand uncertainty, while Data Scientists utilize a broader set of skills including programming, data analysis, and machine learning to extract insights from data. Both roles often overlap but serve different primary purposes within data-driven organizations.

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Probabilistic Modeling jobs near you
Quantitative Risk Modeler

Quantitative Risk Modeler

Seneca Resources, LLC

Vienna, VA • On-site

$77/hr

Other

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

Job description

Title: Quantitative Risk Modeler
Location: Vienna, VA OR Winchester, VA OR Pensacola, FL
Job Type: Contract (extensions expected)
Years of Experience: 10+ years and/or doctorate degree required
Pay Rate:
Pensacola Pay : $60/hr on W2 or $72/hr on C2C
Winchester Pay : $63.00/hr on W2 or  $71/hr on C2C
Vienna Pay:$70/hr on W2 or $77/hr on C2C
 

Role Summary

This is a senior-level (10+ years / PhD) position focused on quantitative modeling for cybersecurity risk. It blends:

  • Advanced mathematics & statistics
  • Machine learning & probabilistic modeling
  • Cybersecurity analytics
  • Data engineering + visualization
Core Responsibilities (implied)

Although not explicitly listed, based on the requirements, you’d likely:

  • Build risk models using probability, statistics, and ML
  • Apply game theory to simulate attacker vs defender scenarios
  • Analyze large datasets (cyber/security data)
  • Design data pipelines and models
  • Create dashboards and visualizations for leadership
  • Translate complex technical insights into business decisions
Required Qualifications

Very high bar:

  • PhD in Mathematics, Physics, or Statistics (or equivalent deep experience)
  • 10+ years of experience
Strong theoretical background in:
  • Probabilistic theory
  • Dynamic systems
  • Statistical modeling
  • Machine learning algorithms
Technical Skills

You’re expected to be very strong in:

  • Programming: Python, SQL
  • Tools: Jupyter Notebook / VS Code
  • Data concepts:
    • Data modeling
    • Data mining
    • Database design
  • Visualization:
    • Strategy + tools like Power BI, Plotly
Advanced / Niche Expertise

This is what makes the role elite-level:

  • Game Theory (important!)
    • Bayesian games
    • Nash equilibrium
    • Algorithmic game theory
  • Cybersecurity knowledge:
    • Security frameworks
    • Risk analytics
Soft Skills

They emphasize:

  • Communication with both technical & non-technical stakeholders
  • Presentation skills (likely reporting to leadership)
  • Ability to simplify complex models into actionable insights.


About Seneca Resources:
Seneca Resources is client driven provider of strategic Information Technology consulting services and Workforce Solutions to government and industry. Seneca Resources is a leading IT services provider with offices in Reston, Virginia, Alabama and Columbia, Maryland that service clients throughout the United States. The key to our success lies within our strong corporate culture which drives our business. We challenge our staff through engaging work, and we reward our staff through competitive compensation, extensive professional training, and excellent opportunities for career advancement. In turn, we look for only the best and brightest to join our team. We are an Equal Opportunity Employer and value the benefits of diversity in our workplace.

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