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Probabilistic Modeling Jobs (NOW HIRING)

OdysseyRe

AVP, Data Analytics and Underwriting

Stamford, CT · On-site

$201.50K - $215K/yr

... probabilistic modeling, experience and exposure rating, and PML estimation; designing and implementing actuarial pricing frameworks and underwriting guidelines for global platforms; and developing ...

ISEE

Research Scientist - Machine Learning

Robotics, Artificial Intelligence, Machine Learning, Perception, Modeling, Simulation, Applied Mathematics, Probabilistic Modeling and Inference or related areas - Collaborating with engineering and ...

Odyssey

AVP, Data Analytics and Underwriting

Stamford, CT · On-site

$201.50K - $215K/yr

... probabilistic modeling, experience and exposure rating, and PML estimation; designing and implementing actuarial pricing frameworks and underwriting guidelines for global platforms; and developing ...

JPL

Senior Master Scheduler V

Pasadena, CA · On-site

Champion best practices in advanced schedule analysis, probabilistic modeling, and quantitative decision support while mentoring junior analysts and strengthening institutional independent assessment ...

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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
Lead Data Scientist, Appraisal & Pricing

Lead Data Scientist, Appraisal & Pricing

Amplio

Denver, CO

Other

Medical, Dental, Vision, PTO

Posted 6 hours ago

Job description

About the Role

Amplio is building the intelligence layer that powers how manufacturers recover value from surplus equipment. You'll lead the development of our appraisal and pricing capabilities - combining data science with agentic AI to automate and improve valuation decisions at scale.

Key Responsibilities

  • Design and iterate models that estimate fair market value, recovery potential, and optimal disposition strategy.
  • Leverage agentic AI to automate cataloging and appraisal workflows.
  • Support Sales to underwrite buyout offers and predict consignment recovery and capacity utilization.
  • Build feedback loops for continuous price optimization and model refinement.
  • Collaborate with Product and Ops to turn insights into high-impact pricing and sourcing actions.

Requirements

What You Bring

  • 4-8+ years in data science, analytics, or preferably pricing within marketplaces, logistics, or asset-heavy environments.
  • Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling).
  • Comfort operating with limited data - capable of building and validating proxy-based models.
  • Blend of technical depth and business intuition; fluent in assumptions, risk, and real-world tradeoffs.
  • Curiosity for manufacturing, recommerce, and the circular economy.

Benefits

  • Early-hire equity
  • Best Medical / Dental / Vision plans
  • Parental benefits
  • Flexible PTO
  • Various stipends
  • Clear work-life boundaries

Apply