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Probabilistic Modeling Jobs in Kentucky (NOW HIRING)

... models leverage meaningful scientific features rather than spurious correlations.* Assess the quality, completeness, and limitations of available data.* Apply statistical, probabilistic, and ...

... models for lead prioritization, partner segmentation, location-based targeting, and behavior forecasting. Apply advanced techniques such as probabilistic matching, multi-touch attribution, and ...

$188K - $230K/yr

Define and evolve attribution models suited to modern privacy environments (e.g., multi-touch, probabilistic, MMM). * Integrate data from ad platforms, MMPs, behavioral telemetry, and product systems ...

$90K - $119K/yr

By bringing the expertise, technology, and business model of the 21st century's most innovative ... Design and implement robust filters, estimators, and probabilistic reasoning systems that enable ...

Ensure the platform remains model-agnostic and capable of taking advantage of rapid advances in ... Build systems that make probabilistic AI useful inside environments that require deterministic ...

$87K - $123K/yr

BEV feature based, Vision-Language-Action Model) (Preferred: Perception/Localization Engineer) * Understanding of probabilistic filtering (e.g., Kalman Filter, Particle Filter) and nonlinear ...

... probabilistic analysis, and technology prioritization. Bringing programs from initiation through ... Mass modeling and vehicle closure of aerospace vehicles and architectures * Trajectory design and ...

By bringing the expertise, technology, and business model of the 21st century's most innovative ... Design and implement robust filters, estimators, and probabilistic reasoning systems that enable ...

$123K - $168K/yr

Our current expertise spans IBR/EMT modeling and simulation, Synchrophasor/PMU analytics, ML/AI applications, and probabilistic/risk analysis. We're looking for another talent with a strong ...

$200K - $300K/yr

Since then we've grown revenue 5x, built a new foundation model for human behavior that has run ... The job is to make probabilistic concepts like populations, uncertainty, and confidence ...

Including knowing when a deterministic workflow is the better answer than probabilistic and when to ... Prompt injection defense, PII handling, model drift and poisoning detection, output validation ...

Ability to explain linkage analysis, Hardy-Weinberg equilibrium, and gene regulation models while ... Emphasizes probabilistic reasoning and connects genetics to genetic counseling, forensic science ...

$170K - $190K/yr

... models, integrating novel perception pipelines seamlessly into the core production codebase ... Strong mathematical foundation in linear algebra, geometry, and probabilistic robotics.

New

$191K - $253K/yr

... probabilistic reasoning systems that enable actionable insights from noisy, ambiguous, or incomplete sensor data. * Analyze system performance using high‑fidelity simulations, innovative modeling ...

$150K - $277K/yr

A clear understanding of the basic elements of a Large Language Model as it exists today, why it ... probabilistic inference and deterministic software systems At Apple, base pay is one part of our ...

$77K - $105K/yr

... and probabilistic methods, and maintaining mapping infrastructure at scale. * Develop and run ... Experience with entity resolution, ontology design, or semantic data modeling across structured and ...

$84K - $101K/yr

Proven experience with Entity Resolution or Record Linkage (e.g., using tools like Senzing, Quantexa, or custom probabilistic matching models) * Schema Design: Ability to design flexible ontologies ...

$220K - $292K/yr

... probabilistic reasoning systems that enable actionable insights from noisy, ambiguous, or incomplete sensor data. * Analyze system performance using high-fidelity simulations, innovative modeling ...

Integrate large language models and build retrieval-augmented generation pipelines over approved ... Create deterministic and probabilistic evaluation automation that measures accuracy, completeness ...

Showing results 21-40

Probabilistic Modeling information

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 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 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.

What are popular job titles related to Probabilistic Modeling jobs in Kentucky?

For Probabilistic Modeling jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Probabilistic Modeling jobs in Kentucky look for?

The top searched job categories for Probabilistic Modeling jobs in Kentucky are:

What cities in Kentucky are hiring for Probabilistic Modeling jobs?

Cities in Kentucky with the most Probabilistic Modeling job openings:

Infographic showing various Probabilistic Modeling job openings in Kentucky as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 17% Full Time, 66% Part Time, 3% Temporary, and 12% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Principal Applied Scientist - TS/SCI

On-site

MAXAR TECHNOLOGIES, INC.
Space Research Administration • 1 - 5K employees

Other

Retirement

Posted 24 days ago


Job description

## Principal Applied Scientist - TS/SCIApplylocations: Herndon, VAtime type: Full timeposted on: Posted Todayjob requisition id: R24414Vantor 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/careersThe application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.The date of posting can be found on Vantor's Career page at the top of each job posting.To apply, submit your application via Vantor's Career page.**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.** #J-18808-Ljbffr

Maxar Technologies logo

About Maxar Technologies

Sourced by ZipRecruiter

Maxar Technologies, headquartered in Denver, CO, US, is a space technology company established in 1969. Operating in the Aerospace Industry, Maxar's key areas of business include Earth Intelligence and Space Infrastructure. The products they offer are critical for global communications, environmental monitoring, national security, intelligence operations, disaster response, and more. Passionate about unlocking the potential of space, Maxar's mission is "to build a better world by harnessing space technology". The company prides itself on advancing state-of-the-art technology, delivering exceptional customer service, and driving growth.

Industry

Space research administration

Company size

1,001 - 5,000 Employees

Headquarters location

Denver, CO, US

Year founded

1969