Principal Applied Scientist - TS/SCI

Vantor Inc.; Herndon (VA); On-site; USD 140,000 - 206,000; Full time

Benefits offered by this job

401k with company match

Student loan repayment assistance

Adoption reimbursement

Pet insurance

Job summary

Vantor is seeking a Principal Applied Scientist for leadership in computational modeling and simulation within a UTS environment. You will work with data scientists, ML engineers, software developers, and operators to build high-fidelity models and validate scientific assumptions for risk assessment and mission survivability.

The role requires a TS/SCI clearance, a strong background in physics/math and Python, and the ability to communicate complex results clearly.

Qualifications

• U.S. Citizen with an active TS/SCI clearance and ability to obtain CI Poly.
• 12+ years of relevant experience.
• Master's or PhD in physics, mathematics, statistics, operations research, engineering, science, or related discipline.
• Strong technical leadership experience.
• Extensive knowledge of process, predictive, physics-based, and agent-based modeling.
• Recent experience (within last 2 years) modeling with statistics and physics-based sensor assessment.
• Experience working with diverse data sets from UTS relevant sources.
• Proficiency in Python and scientific computing libraries.
• Experience AI/ML programs.
• Ability to clearly communicate technical concepts in writing and verbally.
• Must be able to work on-site in Herndon, VA.

Responsibilities

• Serve as the scientific lead for computational modeling and simulation activities across the program.
• Establish scientifically rigorous methodologies for representing UTS phenomena within analytical and simulation environments.
• Ensure analytical approaches reflect the data's physical, operational, and statistical characteristics.
• Design, develop, and validate complex agent-based models representing UTS interactions and environments.
• Develop agent behaviors, environmental conditions, interaction rules, and emergent system dynamics.
• Evaluate simulation outputs for realism, repeatability, and operational relevance.
• Evaluate government-provided datasets to identify meaningful relationships.
• Develop valid approaches for feature engineering and diagnostic vector identification.
• Collaborate with data scientists to ensure machine learning uses meaningful features.
• Assess data quality, completeness, and limitations.
• Apply statistical, probabilistic, and computational methods to characterize uncertainty and system behavior.

Skills

Python

AI/ML

Agent-based modelling

Leadership

Data analysis

Education

Master's or PhD in physics, mathematics, statistics, operations research, engineering, science, or related discipline

Tools

Python libraries

Job description

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what's happening now and shape what's coming next. Vantor is a place for problem solvers, changemakers, and go-getters-where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.

To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status.

Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).

Please review the job details below.

This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI polygraph.

Project

The team will design, develop, validate, and demonstrate an integrated analytical capability supporting pattern recognition, anomaly detection, predictive analytics, agent-based modeling (ABM) or equivalent, and decision support in a Ubiquitous Technical Surveillance (UTS) environment. The effort will enhance Joint Force survivability by enhancing the characterization of the UTS threat and providing a mission-agnostic risk-management tool for commanders and operators to utilize across the spectrum of conflict. The enterprise will leverage this analysis and these tools to increase isolated personnel (IP) survivability by enhancing evasion training, planning, and execution, while bolstering force protection for PR task forces.

The Principal Applied Scientist serves as the scientific authority for the development, validation, and application of advanced analytical and simulation models supporting characterization of the Ubiquitous Technical Surveillance (UTS) environment. This individual combines expertise in computational modeling, applied mathematics, physics, and data science to ensure that machine learning models, agent-based simulations, and analytical frameworks accurately represent real-world phenomena and produce scientifically defensible, operationally relevant results.

Working closely with data scientists, machine learning engineers, software developers, and operational subject matter experts, the Principal Applied Scientist is responsible for developing high-fidelity models, validating scientific assumptions, assessing uncertainty, and ensuring that analytical outputs accurately characterize UTS risks and mitigation strategies. This role is instrumental in delivering a transition-ready capability that enables commanders and operators to evaluate operational risk and improve mission survivability.

Responsibilities

• Serve as the scientific lead for computational modeling and simulation activities across the program.
• Establish scientifically rigorous methodologies for representing UTS phenomena within analytical and simulation environments.
• Ensure analytical approaches accurately reflect the underlying physical, operational, and statistical characteristics of the data.
• Design, develop, and validate complex agent-based models representing UTS interactions and operational environments.
• Develop agent behaviors, environmental conditions, interaction rules, and emergent system dynamics
• Evaluate simulation outputs for realism, repeatability, and operational relevance.
• Evaluate government-provided datasets to identify meaningful physical, temporal, behavioral, and operational relationships.
• Develop scientifically valid approaches for feature engineering and diagnostic vector identification.
• Collaborate with data scientists to ensure machine learning models leverage meaningful scientific features rather than spurious correlations.
• Assess the quality, completeness, and limitations of available data.
• Apply statistical, probabilistic, and computational methods to characterize uncertainty and system behavior.

Minimum Qualifications

• US Citizen and must have an active TS/SCI clearance, with ability to obtain CI Poly.
• 12+ years of relevant experience.
• Master's or PhD in physics, mathematics, statistics, operations research, engineering, science, or related discipline.
• Strong technical leadership experience.
• Extensive demonstrated knowledge and experience utilizing the following modeling techniques: process, predictive, physics-based, agent-based.
• Significant current experience (i.e., within last 2 years) in modeling, using statistics to conduct predictive modeling and make estimates on future occurrences based on prior events, and using physics-based modeling to review sensor capabilities and predict sensor ability to perform tasks in a synthetic scenario
• Experience working with diverse data sets from UTS relevant sources
• Proficiency in Python and scientific computing libraries.
• Experience AI/ML programs.
• Ability to clearly communicate technical concepts and analytical results in writing and verbally.
• Must be able to work on-site in Herndon, Va.

Preferred Qualifications

• Experience with agent-based modeling.
• Experience supporting operational environments and/or Government R&D projects.
• published modeling reports and/or authored new procedures/methods to create innovative modeling approaches to solve complex issues
• Experience modeling human behavior, adversarial systems, or complex adaptive systems.
• Experience with reinforcement learning, Bayesian inference, Monte Carlo methods, or stochastic simulation.
• Familiarity with explainable AI (XAI) and integrating scientific principles into machine learning workflows.
• Experience developing digital twins or high-fidelity operational simulations.
• Experience supporting personnel recovery, force protection, intelligence analysis, or mission planning.

Pay Transparency

To support pay transparency, Vantor includes salary ranges in all U.S. job postings. Starting pay for this role will fall within the listed range and will be based on factors such as experience, qualifications, skills, location, and market conditions. Candidates who meet the minimum requirements for the role should not expect to receive compensation at the top of the range. The listed range reflects the expected pay for this position, and final offers will be determined based on each candidate's experience, expertise, and alignment with the role.

* The base pay for this position within the Washington, DC metropolitan area is: $140,000.00 - $187,000.00 - $205,700.00 annually.

For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range.

Benefits

Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at: https://www.Vantor.com/careers

EEO Policy

Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.