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Entry Level Stochastic Modeling Jobs (NOW HIRING)

Americanfidelity

Data Scientist

Oklahoma City, OK · Hybrid

Strong background in modeling large scale discrete, nonlinear or stochastic mathematical ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

American Fidelity

Data Scientist

Oklahoma City, OK · On-site

Strong background in modeling large scale discrete, nonlinear or stochastic mathematical ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

All JobsStochastic Modeling JobsEntry Level Stochastic Modeling Jobs

Entry Level Stochastic Modeling information

See salary details

$25K

$47.8K

$68.5K

How much do entry level stochastic modeling jobs pay per year?

As of Sep 4, 2026, the average yearly pay for entry level stochastic modeling in the United States is $47,831.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,500.00 and $52,000.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Stochastic Modeling vs Entry Level Data Analysis?

AspectEntry Level Stochastic ModelingEntry Level Data Analysis
Required CredentialsBachelor's in Math, Statistics, or related field; basic programming skillsBachelor's in Data Science, Statistics, or related field; proficiency in Excel and SQL
Work EnvironmentFinancial firms, insurance, or research institutions focusing on probabilistic modelsBusiness, marketing, or tech companies analyzing datasets for insights
Employer & Industry UsageUsed in finance, insurance, and risk management sectorsUsed across various industries including retail, healthcare, and tech

Entry Level Stochastic Modeling focuses on developing probabilistic models to assess risk and uncertainty, often in finance or insurance. Entry Level Data Analysis involves examining datasets to identify trends and support decision-making across diverse industries. While both roles require analytical skills, stochastic modeling emphasizes mathematical and statistical modeling, whereas data analysis centers on data interpretation and visualization.

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 Entry Level Stochastic Modeling jobs look for?

The top searched job categories for Entry Level Stochastic Modeling jobs are:

Entry Level Stochastic Modeling jobs near you
Infographic showing various Entry Level Stochastic Modeling job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $47,831 per year, or $23 per hour.

Data Scientist

Americanfidelity

Oklahoma City, OK • Hybrid

Full-time

Posted 21 days ago

Job description

Job Description:

Work with large, complex data sets using to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed to complete end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Engineer analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed in systems, products and processes.

Research and engineer analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence and optimization methods to improve the quality of products; example application areas include customer segmentation modeling and end-user behavioral modeling/prediction.

Technical Skills and Requirements:

  • Expert in multiple statistical software (e.g., R, Python, Julia, MATLAB, pandas) and associated data science libraries (scikit-learn).
  • Expert in database languages (e.g., SQL).
  • Experience creating meaningful data visualizations and/or interactive dashboards that communicate findings and business impacts using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js.
  • Applied experience with machine learning on large datasets using Big Data tools such as Apache's Hadoop or Spark
  • Expert in deep learning techniques and neural networks using languages such as as TensorFlow
  • Expert in multiple major programming language (C/C++. C#, Java, Python, etc.) or optimization modeling languages (AMPL, GAMS, AIMMS, OPL, etc.)
  • Experience with data science methods related to data architecture, data cleaning, data and feature engineering, and predictive analytics.
  • Strong background in modeling large scale discrete, nonlinear or stochastic mathematical optimization models and engineering efficient optimization algorithms.
  • Familiarity with natural language processing, machine learning, statistical modeling, predictive modeling, and hypothesis testing.
  • Familiarity working with both structured and unstructured data, including textual data.
  • Ability to work in a fast-paced environment.
  • Exceptionally strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.
  • Exceptional analytical thinking and problem solving skills.
  • Exceptional understanding of business and business strategy.
  • Exceptional planning skills.
  • Exceptional organizational skill and ability to work autonomously.

Education:

Master's degree in related field required.

Location:

This is a hybrid position. Applicants must be located in OKC Metro area or willing to relocate.

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