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Stochastic Modeling Jobs (NOW HIRING)

Software Technology Inc

AI ML Engineer

Charlotte, NC · On-site

Knowledge of Monte Carlo simulations and stochastic modeling * Experience with Git and CI/CD pipelines * Exposure to regulatory frameworks Solvency II, IFRS 17 Soft Skills * Strong problem-solving ...

Software Technology Inc

AI ML Engineer

Dallas, TX · On-site

Knowledge of Monte Carlo simulations and stochastic modeling * Experience with Git and CICD pipelines * Exposure to regulatory frameworks Solvency II, IFRS 17 Soft Skills * Strong problem solving and ...

Samprasoft

AI ML Engineer

Dallas, TX · On-site

Knowledge of Monte Carlo simulations and stochastic modeling * Experience with Git and CI/CD pipelines * Exposure to regulatory frameworks Solvency II, IFRS 17 Soft Skills * Strong problem solving ...

Tecolote Research

Senior Cost Analyst

Arlington, VA · On-site

$96.10K - $121.90K/yr

Stochastic modeling and have an understanding of how to apply sophisticated statistical and analytical techniques and convey the meaning of the results to DOD decision makers * A secret-level ...

Cint

Data Scientist

Manhattan, NY · On-site

... modeling, classification, stochastic modeling/simulation, and more). Exposure to a variety of machine learning methods (clustering, regression, tree-based models, etc.) and their real-world ...

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How much do stochastic modeling jobs pay per year?

As of Jun 4, 2026, the average yearly pay for stochastic modeling in the United States is $104,419.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,500.00 and $128,000.00 per year, depending on experience, location, and employer.

What is a Stochastic Modeling job?

A Stochastic Modeling job involves developing mathematical models that incorporate randomness to analyze uncertain systems and predict outcomes. Professionals in this field apply probability theory, statistics, and computational techniques to fields such as finance, insurance, engineering, and data science. They build and validate models to assess risks, optimize decision-making, and improve forecasting accuracy. Strong analytical skills and proficiency in programming languages like Python, R, or MATLAB are often required.

What are the key skills and qualifications needed to thrive in the Stochastic Modeling position, and why are they important?

To thrive in stochastic modeling, you need strong mathematical and statistical skills, often backed by a degree in mathematics, statistics, data science, or a related field. Expertise with technical tools such as R, Python, MATLAB, and statistical modeling software, as well as familiarity with industry-standard certifications like FRM or CFA in finance, is highly valued. Analytical thinking, attention to detail, and the ability to communicate complex ideas to non-technical stakeholders are critical soft skills. These competencies allow you to create accurate models for forecasting and risk assessment, helping organizations make informed decisions in uncertain environments.

What are some typical daily responsibilities for a professional in stochastic modeling?

As a stochastic modeling professional, your daily tasks might include developing and validating probabilistic models, analyzing large datasets, and performing simulations to forecast outcomes or assess risks. You’ll often collaborate with cross-functional teams such as data scientists, financial analysts, or engineers to translate real-world problems into mathematical frameworks. Regular responsibilities also involve presenting findings to stakeholders, refining models based on new data, and staying updated on the latest modeling techniques in your industry. This role provides a balance of independent analytical work and teamwork, offering diverse challenges and skill development opportunities.

What jobs make 3000 a month without a degree?

In stochastic modeling or related fields, entry-level roles such as data analysts, financial analysts, or junior quantitative analysts can sometimes earn around $3,000 per month without a degree, especially with relevant skills in programming, statistics, and software tools like Excel or Python. Many of these positions value practical experience and certifications over formal education, and remote or freelance opportunities may also meet this income level.
More about Stochastic Modeling jobs
What are the most commonly searched types of Stochastic Modeling jobs? The most popular types of Stochastic Modeling jobs are:
What job categories do people searching Stochastic Modeling jobs look for? The top searched job categories for Stochastic Modeling jobs are:
Stochastic Modeling jobs near you
Infographic showing various Stochastic Modeling job openings in the United States as of May 2026, with employment types broken down into 81% Full Time, 6% Part Time, and 13% Contract. Highlights an 87% In-person, and 13% Hybrid job distribution, with an average salary of $104,419 per year, or $50.2 per hour.
AI ML Engineer

AI ML Engineer

Software Technology Inc

Charlotte, NC • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Data Scientist

We are seeking a highly analytical and detail-oriented Data Scientist to join our team in the reinsurance domain. The ideal candidate will leverage data to drive insights into risk modeling, pricing strategies, claims analysis, and portfolio optimization. This role requires strong technical expertise, business acumen, and the ability to communicate complex findings clearly.

Technical Skills Primary
  • Programming Languages: Python, Pandas, NumPy, Scikitlearn, SQL
  • Statistical Modeling: Machine Learning, Regression, Classification, Clustering, Time Series Forecasting
  • Data Visualization: Power BI, Tableau, Matplotlib, Seaborn
  • Big Data Technologies: Spark, Hadoop (basic understanding)
  • Cloud Platforms: Azure or AWS (especially for data pipelines and model deployment)
  • Data Engineering: ETL processes, data wrangling, and feature engineering
  • Insurance/Reinsurance Domain Knowledge: Exposure to actuarial models, risk assessment, and claims analytics
Technical Skills Secondary (Nice to Have NOT Mandatory)
  • R or SAS for statistical analysis
  • Experience with Natural Language Processing (NLP)
  • Familiarity with geospatial data and mapping tools
  • Knowledge of Monte Carlo simulations and stochastic modeling
  • Experience with Git and CI/CD pipelines
  • Exposure to regulatory frameworks Solvency II, IFRS 17
Soft Skills
  • Strong problem-solving and critical thinking abilities
  • Excellent communication and storytelling skills for non-technical stakeholders
  • Collaborative mindset with cross-functional teams (actuarial, underwriting, IT)
  • Ability to manage multiple projects and prioritize effectively
  • Curiosity and continuous learning attitude
  • High attention to detail and data integrity

Qualifying Questions

Can you describe a project where you applied machine learning to solve a business problem in the insurance or financial domain?

How do you ensure the quality and reliability of your data before building models?

Have you worked with actuarial teams or underwriting departments before? If yes, how did you contribute to their decision-making process?

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