Mathematics & Python Expert - Freelance AI Trainer

Mindrift

While each project involves unique tasks, contributors may:

• Design original computational mathematics problems that simulate real mathematical research workflows;
• Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy);
• Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks);
• Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis;
• Base problems on real research challenges or practical applications from mathematical practice;
• Verify solutions using Python with standard mathematical libraries;
• Document problem statements clearly and provide verified correct answers.

This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:

• Degree in Mathematics (Pure or Applied) or related fields;
• Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent;
• 2+ years of professional experience: applied, research, or teaching experience is applicable;
• Experience with numerical methods and symbolic computation;
• Ability to design problems that mirror real mathematical research workflows;
• Familiarity with computational complexity theory;
• Strong written English (C1+).

For this project, tasks are estimated to require around 10 20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.

On this project, contributors can earn up to $35 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.