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Probabilistic Modeling Jobs in Kentucky (NOW HIRING)

ClifyX

Decision Intelligence Engineer

Louisville, KY · On-site

... probabilistic modeling, databricks, Ray RLLib, Gymnasium, PettingZoo (MARL). Company : ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability ...

International Executive Service Corps

Knowledge in industry consensus standards for Probabilistic Risk Assessment (PRA), including ASME/ANS RA-S-1.4. * Skill in PRA model development, plant operating state definition, initiating event ...

Neara

Extensive experience in probabilistic modeling, uncertainty quantification, model validation, scientific computing capabilities and decision-making under incomplete information. * Substantial ...

Calix

... and probabilistic modeling to real-world broadband data Calix Cloud - Platform & Scale Collaborate with data engineering and platform teams to develop and integrate models into Calix Cloud's cloud ...

Far Coder

$90K - $119K/yr

Design systems that gracefully handle the probabilistic and non-deterministic behavior of AI models * Work with clinical and operational data across structured and unstructured formats, including ...

Trading Interview

Design and develop complex models to generate real-time fair values for intricate, uncertain domains (e.g., weather, event-driven outcomes, or probabilistic systems) * Identify edge cases, structural ...

Altamira Technologies Corp.

$64K - $78K/yr

Develop and refine probabilistic algorithms, statistical models, and hypothesis tests for feature-based change detection and mission-data analysis. * Support radar-data processing and change ...

Neura Market

$191K - $253K/yr

By bringing the expertise, technology, and business model of the 21st century's most innovative ... Sound judgment about where probabilistic AI is appropriate and where deterministic software or ...

Electric Power Research Institute, Inc.

EPRI seeks an experienced engineer with expertise in Probabilistic Risk Assessment (PRA), risk ... of PRA models addressing internal events, flooding, external hazards, and integrated risk ...

Boyd Corporation

$95K/yr

Deep proficiency in probabilistic risk assessment (PRA), Monte Carlo simulations, and reliability modeling software (e.g., ReliaSoft, Item ToolKit, or PTC Windchill). * 5+ years analyzing and ...

Zurich 56 Company Ltd

Building and/or enhancing models for crop insurance business * Identify and integrate external data ... Experience applying data transformation techniques such as exact and probabilistic matching methods ...

Dynata

... probabilistic matching techniques. Design graph structures that support downstream analytics ... Forecasting & Predictive Modeling Build and maintain forecasting models for supply prediction ...

Peraton

$91K - $120K/yr

Ability to develop digital models using virtualization tools (e.g., QEMU) and network them together ... Artificial intelligence (reasoning, probabilistic inference, machine learning In this position, as ...

International Consulting Associates, Inc

$93K - $123K/yr

Experience defining measurable acceptance criteria for probabilistic features such as model outputs, alerts, recommendations, or rankings. * Strong understanding of data pipelines, APIs, data quality ...

El Camino Health

Conduct sensitivity analyses, scenario modeling, and probabilistic analyses (PSA) consistent with HTA standards. Statistical Programming & Data Infrastructure * Serve as the primary statistical ...

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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:

Probabilistic Modeling jobs near you
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.

Decision Intelligence Engineer

Louisville, KY • On-site

ClifyX
Recruiting and Staffing Services • 51 - 200 employees
Learn more about ClifyXexternal

Full-time

Re-posted 26 days ago

Job description

Job Summary:
ClifyX is seeking a Decision Intelligence Engineer to build and deploy enterprise-scale decision systems. The role requires hands-on experience with various reinforcement learning methods and a deep understanding of decision-making frameworks.
Qualifications:
Required:
• 3+ years building and deploying enterprise scale decision systems.
• Hands-on experience with implementing policy gradient methods (PPO, A3C), value-based approaches (DQN, Q-learning) and off-policy algorithms.
• Deep familiarity with the Bellman equation, reward shaping, exploration-exploitation tradeoff, constraint mapping and knowing common failure points of real-world reinforcement learning systems.
• Ability to diagnose issues with policy learning and collapse, credit assignment issues, and distributional shifts affecting performance of the model.
• Deep learning frameworks (tensorflow, pytorch), linear programming, Markov decision processes, Actor-Critic methods, Offline RL methods (CQL, Decision Transformer), probabilistic modeling, databricks, Ray RLLib, Gymnasium, PettingZoo (MARL).
Company:
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations. Founded in 1998, the company is headquartered in South Plainfield, USA, with a team of 501-1000 employees. The company is currently Late Stage.
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About ClifyX

Sourced by ZipRecruiter

ClifyX is a well-established player in the IT Services sector that specializes in providing result-oriented technological solutions to a wide range of industrial verticals. Based in South Plainfield, New Jersey, ClifyX offers a comprehensive selection of IT services that include project staffing, application development, professional consulting, and other IT-based solutions. While the company's website, clifyx.com, does not divulge the exact founding date, it is clear that ClifyX has grown into a renowned name within their domain, thanks to their unwavering commitment to innovative practices. The company's mission statement revolves around harnessing the power of technology to assist their clientele in steering their respective businesses towards success.

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

South Plainfield, NJ, US

Year founded

1998

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