Computational Statistics and Applied Mathematics Expert (R, Python, and Matlab/Scilab)

About this role

You will design advanced computational statistics and applied mathematics problems for a large-scale AI evaluation benchmark. The role involves creating original graduate- and research-level tasks based on realistic statistical and mathematical workflows, including simulation, numerical computation, optimization, statistical modelling, differential equations, Bayesian inference, spatial analysis, time-series modelling, and scientific computing. You will test tasks against state-of-the-art AI models and refine them until they reach the required level of difficulty, reproducibility, and technical rigor.

Computational Statistics AI Expert

Responsibilities

• Computational task design: Create original research-level statistical and applied mathematics problems using specialized scientific software.
• Statistical modelling: Develop tasks involving Bayesian statistics, psychometrics, structural equation modelling, regression, survival analysis, time series, spatial statistics, and statistical learning.
• Mathematical modelling: Build problems involving differential equations, dynamical systems, optimization, numerical linear algebra, computational geometry, and high-precision computation.
• Scientific programming: Develop problem setups, oracle functions, numerical workflows, and automated solution validators using Python and other relevant tools.
• Software-based workflows: Design tasks requiring expert use of specialized R, Python, Matlab, or Scilab packages

Qualifications

• Master’s or PhD in Statistics, Applied Mathematics, Computational Mathematics, Data Science, Econometrics, Operations Research, or another closely related quantitative/STEM field.
• PhD preferred, or Master’s degree with approximately 10+ years of relevant professional or research experience.
• Proven proficiency with at least one specialized statistical, mathematical, or scientific software package demonstrated through publications, open-source contributions, research, or professional work.
• Strong hands-on experience with specialized R, Python, Matlab, or Scilab tools rather than theoretical knowledge alone.
• Strong Python programming skills for developing problem setups, oracle functions, numerical workflows, and solution validators.