About the job
We invite you to submit your CV in English, highlighting your English proficiency level.
Mindrift collaborates with talented professionals to connect them with project-based AI opportunities in leading tech firms, focusing on the assessment, evaluation, and enhancement of AI systems. This is a project-based engagement, not a permanent position.
Key Responsibilities:
- Craft original computational statistics challenges that emulate real-world mathematical research workflows.
- Develop problems that necessitate Python programming for solutions, utilizing libraries such as Numpy, SciPy, and Sympy.
- Ensure challenges are computationally demanding, requiring extended timeframes to solve manually (days/weeks).
- Formulate problems that necessitate complex reasoning chains within domains like number theory, combinatorics, graph theory, and numerical analysis.
- Base issues on authentic research obstacles or practical applications from mathematical fields.
- Validate solutions through Python, using standard mathematical libraries.
- Clearly document problem statements and provide verified correct answers.
Ideal Candidate Profile:
- A degree in Statistics or a related area.
- Proficient in Python for numerical validation; familiarity with MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, or other programming languages is acceptable.
- At least 2 years of relevant professional experience in applied research or teaching.
- Strong command of written English (C1 or higher).
- Holding professional certifications (e.g., CMME, SAS Certification, CAP) and experience with international or applied projects is advantageous.
Application Process:
Apply → Pass qualifications → Join a project → Complete tasks → Get compensated.
Project Commitment:
Tasks are expected to require approximately 10–20 hours per week during active phases, depending on project needs. This is an estimate and not a guaranteed workload.
Compensation:
Contributors can earn up to $73 per hour, contingent upon their contribution level and pace. Compensation varies across projects based on their scope, complexity, and required expertise; other projects may offer different earning potential based on their specific requirements.
