Actuarial Research Assistant - Math and Statistics Department

Bowling Green State University; Bowling Green (OH); On-site; USD 21,000 - 30,000; Part time

Job summary

Bowling Green State University seeks an Actuarial Research Assistant to support faculty research in actuarial science, risk sharing, and machine learning. The student will help generate data, perform numerical analyses, and apply statistical methods to evaluate risk reduction.

The position involves preparing figures and summaries, using R or Python, attending regular research meetings, and maintaining reproducible research files with deadlines for Fall 2026 and Honda AI+X Final Showcase in

Qualifications

• Currently enrolled undergraduate student in Actuarial Science at Bowling Green State University.
• Junior or senior standing preferred.
• Completion of or substantial preparation for MATH 4440, MATH 4260, and MATH 4270.

Responsibilities

• Assist with faculty-led research in actuarial science, peer-to-peer insurance, and network-based risk sharing.
• Generate and organize numerical and simulated data for network-based risk-sharing models.
• Compute and summarize structural characteristics of networks and evaluate risk-sharing outcomes.
• Apply statistical and machine-learning methods (regression, random forests, boosting) to analyze and predict risk-reduction measures.
• Conduct numerical analysis and assist with model evaluation and interpretation of results.
• Use R, Python, or related computational tools to implement research methods and manage data.
• Prepare figures, tables, and concise summaries of research findings.
• Participate in regular meetings with the faculty supervisor and incorporate feedback.
• Maintain organized and reproducible research files, code, and documentation.
• Perform other research-related duties as assigned.

Skills

Initiative to learn new tools

Clear communication

Information gathering

Task decomposition

Learning new software

Education

Undergraduate student in Actuarial Science at BGSU

Junior or senior standing preferred

Math coursework: MATH 4440/4260/4270

Tools

R

Python

Job description

The Actuarial Research Assistant will support faculty research in actuarial science, risk sharing, and machine learning. The student will assist with data generation, numerical analysis, network-based risk-sharing models, and the application of statistical and machine-learning methods to evaluate and predict risk reduction. The position may also involve preparing figures, tables, and summaries of research results.

Career Readiness Competencies

• Take initiative to learn new tools, systems, or procedures on the job.
  
• Present ideas or updates in a clear and organized manner.
  
• Identify when additional information is needed before making a decision.
  
• Break down tasks into steps to complete work more efficiently.
  
• Learn new software or digital platforms as needed for your role.

• Assist with faculty-led research in actuarial science, peer-to-peer insurance, and network-based risk sharing.
• Generate and organize numerical and simulated data for network-based risk-sharing models.
• Compute and summarize structural characteristics of networks and evaluate corresponding risk-sharing outcomes.
• Apply statistical and machine-learning methods, including regression, random forests, and boosting methods, to analyze and predict risk-reduction measures.
• Conduct numerical analysis and assist with model evaluation, validation, and interpretation of results.
• Use R, Python, or related computational tools to implement research methods and manage data.
• Prepare figures, tables, and concise summaries of research findings.
• Participate in regular meetings with the faculty supervisor, provide progress updates, and incorporate feedback into ongoing work.
• Maintain organized and reproducible research files, code, and documentation.
• Perform other research-related duties associated with the project as assigned.

• Currently enrolled as an undergraduate student in Actuarial Science at Bowling Green State University.
• Junior or senior standing preferred.
• Completion of, or substantial preparation equivalent to, MATH 4440, MATH 4260, and MATH 4270.
• Background in probability, statistics, actuarial mathematics, and quantitative analysis.
• Experience with R, Python, or another programming language used for statistical or numerical analysis.
• Familiarity with network-based risk sharing, peer-to-peer insurance, or related network models.
• Ability to work independently, follow research instructions, and meet established deadlines.
• Strong analytical, problem-solving, and communication skills.
• Willingness to learn and apply statistical and machine-learning methods as required by the research project.

• The student should be available to work on the project during Fall 2026 and participate in regular research meetings. Availability to assist with preparation for the Honda AI+X Final Showcase in January 2027 is preferred.
• Applicants should submit a resume and an unofficial transcript or list of completed relevant coursework.