Competitive Data Scientist - Remote

YO AI Labs; New York (NY); Remote; USD 83,000 - 131,000; Part time

Job summary

YO AI Labs is seeking a Competitive Data Scientist to work as a contractor on an AI training project. The role involves creating challenging data science tasks, building reproducible environments, and ensuring robust reference solutions with clear evaluation criteria.

Flexibility and weekend availability are noted as part of the schedule. The candidate should have a background in data science, ML, or applied mathematics, with strong programming skills and experience on platforms like Kaggle,

Qualifications

• Must have strong problem-solving skills and a clear understanding of analytical methods.
• Practical programming skills to implement, test, and verify solutions.
• Experience with competitive data science platforms such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench.

Responsibilities

• Build reproducible environments, prepare datasets and dependencies, and implement reference solutions.
• Develop tests and evaluation criteria to verify solution correctness.
• Run coding agents on tasks, analyze failures, and refine tasks based on observed results.
• Identify implementation errors, flawed assumptions, data leakage, and other correctness issues.
• Document task requirements, solution logic, and verification procedures clearly.

Skills

Problem solving

Programming

Competitive data science platforms

Tools

Kaggle

DrivenData

Zindi

AIcrowd

Numerai

DataSource.ai

CodaLab/Codabench

Job description

Role Title: Competitive Data Scientist

Role Type: Contractor
Location: Global, Fully Remote
Time Commitment: Approximately 15 hours per week
Schedule: Flexible, including weekends

We are seeking Data Scientists, Machine Learning Practitioners, and Applied Mathematics experts with competitive data science experience to support an AI training project. You'll develop challenging, reproducible tasks that test problem-solving, programming, and analytical reasoning. Each task must include a verified reference solution and reliable evaluation criteria.

Key Responsibilities

• Build reproducible environments, prepare datasets and dependencies, and implement reference solutions.
• Develop tests and evaluation criteria to verify solution correctness.
• Run coding agents on tasks, analyze failures, and refine tasks based on observed results.
• Identify implementation errors, flawed assumptions, data leakage, and other correctness issues.
• Document task requirements, solution logic, and verification procedures clearly.

Required Qualifications

• Demonstrated experience in data science, machine learning, quantitative modeling, or research competitions.
• Strong problem-solving skills and a clear understanding of analytical methods.
• Practical programming skills to implement, test, and verify solutions.
• Experience with competitive data science platforms such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench.

Preferred Qualifications

• Strong Python programming skills.
• Experience with testing, debugging, and working with unfamiliar code.