Competitive Data Scientist (Kaggle)

Design rigorous data science and machine learning tasks that draw on competitive modeling experience, mathematical reasoning, and practical programming. Your work will help evaluate whether coding agents can produce correct, reproducible solutions rather than merely plausible answers.

• Build reproducible task environments, including relevant data, dependencies, and verified reference solutions.
• Develop tests and evaluation criteria that distinguish correct solutions from incomplete or flawed approaches.
• Run coding agents against tasks, investigate failures, and refine tasks based on observed behavior.
• Identify implementation errors, flawed assumptions, data leakage, and other issues that affect solution correctness.
• Clearly document task requirements, solution reasoning, and verification steps.

• Demonstrated experience in data science, machine learning, quantitative modeling, or relevant research competitions such as Kaggle or DrivenData.
• Strong problem solving skills and a clear understanding of the methods you use.
• Practical programming ability to implement and verify your own solutions.
• Experience with competitive data science platforms may include Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, CodaLab, or Codabench.
• Strong Python experience, including testing, debugging, and working with unfamiliar code, is a significant advantage.

• Independent contractor engagement.
• Fully remote and open to candidates globally.
• Approximately 15 hours per week.
• Flexible schedule: choose your working hours and days, including weekends if desired.

$60 to $120 per hour.

Apply by email.