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Probabilistic Modeling Jobs in Kentucky (NOW HIRING)

$95 - $145/hr

... and probabilistic tool behavior, and qualifying or validating automation testing frameworks • ... case tracking, model risk classification, and disclosure requirements for GxP systems For ...

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Experience validating AI/ML-enabled systems, distinguishing deterministic and probabilistic tool ... Experience with AI governance processes, including AI use case tracking, model risk classification ...

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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.

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What cities in Kentucky are hiring for Probabilistic Modeling jobs?

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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.

$95 - $145/hr

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Posted 2 days ago

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# System Test and Validation LeadDeloitteFull timeMiami, FLQuality AssurancePosted 1 days agoExpires Sep 17, 2026## Job DescriptionDrive validation and compliance activities for complex GxP systems as a Senior Consultant, Regulatory, Risk, and Compliance. This role supports system validation strategy, audit readiness, CAPA management, and risk-based compliance activities across regulated technology environments. This role helps clients address emerging validation considerations for AI/ML-enabled systems and automation frameworks. If this sounds exciting, then this team may be the right fit for you! Work you'll do As a Senior Consultant, Regulatory, Risk, and Compliance on the Regulatory, Risk, and Forensic team, you will be responsible for... • Lead end-to-end validation activities for GxP systems, including validation plans, IQ/OQ/PQ protocols, summary reports, user requirements specifications, functional specifications, design specifications, and traceability matrices• Apply risk-based validation principles to assess system impact, classify validation requirements, and support compliance with GAMP 5, 21 CFR Part 11, and data integrity expectations• Drive inspection readiness activities, including gap assessments, mock audits, validation package reviews, and support for regulatory inspections and responses• Lead CAPA activities for validation findings, including root cause analysis, effectiveness checks, closure documentation, and tracking of open compliance actions• Validate AI/ML-enabled GxP systems and automation testing frameworks, including development of validation approaches for non-deterministic outputs and documentation of AI governance requirements A successful candidate would possess these skills: • Ability to work independently and collaborate as part of a team• Effective written and verbal communication skills• Meticulous attention to detail and quality of work product• Ability to build and sustain professional relationships• Ability to lead projects or workstreams• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment• Strong interpersonal skills and professional demeanor• Ability to meet deadlines• Ability to provide clear guidance to others The Team Our Deloitte Regulatory, Risk & Forensic team helps client leaders translate multifaceted risk and an evolving regulatory environment into defensible actions that strengthen, protect, and transform their organization. Join our team and use advanced data, AI, and emerging technologies with industry insights to help clients bring clarity from complexity and accelerate their path to value creation. Qualifications Required: • Bachelor's degree in business, information systems, computer science, engineering, or equivalent experience; 6+ years of experience in computer system validation in a life sciences environment, including pharma, biotech, medical device, or clinical• Experience leading validation deliverables for GxP systems, including IQ/OQ/PQ protocols, validation plans, summary reports, user requirements specifications, functional specifications, design specifications, and traceability matrices• Experience applying 21 CFR Part 11, EU Annex 11, GAMP 5, and data integrity requirements, including Attributable, Legible, Contemporaneous, Original, Accurate, Complete, Consistent, Enduring, and Available principles• Experience managing CAPA lifecycle activities and supporting inspection readiness for Food and Drug Administration or European Medicines Agency audits• Experience validating AI/ML-enabled systems, distinguishing deterministic and probabilistic tool behavior, and qualifying or validating automation testing frameworks• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.• Limited immigration sponsorship may be available. Preferred: • Experience supporting periodic review programs for validated systems and associated CAPA triggers• Experience validating cloud or software as a service platforms, including Veeva, ServiceNow, or Salesforce in a GxP environment• Experience working in Agile delivery environments with validation activities embedded in sprints• Experience with AI governance processes, including AI use case tracking, model risk classification, and disclosure requirements for GxP systems For individuals assigned and/or hired to work in a remote role, Deloitte is required by law to include a reasonable estimate of the compensation range for this role. This compensation range is specific to a remote role and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $95,000 to $145,000. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. #J-18808-Ljbffr