Statistics & Python Specialist for AI Research Projects

Explore more jobs; Kuwait City; On-site; KWD 9,800 - 17,000; Part time

Job summary

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focusing on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

For statistics specialists with Python experience, this appears as a part-time, non-permanent role. Tasks include designing computational problems, validating with Python, and clear documentation of solutions.

Qualifications

• Degree in statistics or a related field.
• Proficient Python for numerical validation.
• 2+ years of professional experience in statistics or related roles.
• Certifications (e.g., CMME, SAS) are a plus.

Responsibilities

• Design original computational statistics 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.

Skills

Statistics background

Python proficiency

Problem design

Research experience

Education

Bachelor's degree in statistics or related field

Tools

Python

NumPy

SciPy

SymPy

Pandas

MATLAB

R

C

SQL

Job description

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focusing on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

For statistics specialists with Python experience, this appears as a part-time, non-permanent role. Tasks include designing computational problems, validating with Python, and clear documentation of solutions.