Competitive Data Scientist

About the role

We're looking for data scientists, machine learning practitioners, and applied mathematics experts with competitve Data Science experience. (Kaggle, DrivenData, etc.)

You’ll draw on your competition experience, mathematical reasoning, and programming skills to create tasks that require more than a plausible answer. Each task should have a reproducible environment, a verified reference solution, and reliable checks for successful completion.

Relevant competition platforms include Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, and CodaLab/Codabench.

Scope of Work

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

What you’ll bring

• Demonstrated experience in data science, ML, quantitative modeling, or relevant research competitions. (Kaggle, DrivenData, etc.)
• Strong problem-solving ability and a clear understanding of the methods you use.
• Practical programming ability sufficient to implement and verify your own solutions.

Preferred Qualifications

• Strong coding experience, particularly in Python, including testing, debugging, and working with unfamiliar code

Benefits

Not provided in the source listing.

Schedule and availability

Approximately 15 hours per week. Flexible-you choose the hours and days you work, including weekends if desired

Contract & Payment Terms

• Source posting label: Yesterday, captured 13 October 2026; interpreted as approximately 12 October 2026. Source timezone is unspecified. First published on Remolity on 13 October 2026.

Where you can work

The listing states worldwide eligibility. Confirm work authorization with the employer.

Remote does not always mean work from any country. Always check the employer’s location and working-hour requirements.