Competitive Data Scientist

Requirements

• Competitive Data Science experience (Kaggle, DrivenData, Zindi, AIcrowd, Numerai, or similar)Must
• Data Science expertiseMust
• Machine Learning expertiseMust
• Quantitative modeling or applied mathematicsMust
• Strong problem-solving abilityMust
• Clear understanding of data science and ML methodsMust
• Practical programming ability to implement and verify solutionsMust
• Python programming
• Testing and debugging code
• Working with unfamiliar codebases

What you'll do

• Build reproducible environments and prepare data and dependencies
• Implement reference solutions for data science tasks
• Develop tests and evaluation criteria to verify correctness
• Run coding agents against tasks and investigate failures
• Refine tasks based on observed agent behavior
• Identify implementation errors, flawed assumptions, and data leakage
• Document task requirements, solution reasoning, and verification steps

About the role

Role Title: Competitive Data Scientist Pay: $60–$120/hour Location: Global, fully remote Job Type: Contractor (~15 hours per week) Schedule: Flexible-you choose the hours and days you work, including weekends if desired 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. What You’ll Do • 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 We’re Looking For • 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. Relevant competition platforms include Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, and CodaLab/Codabench. Huge Pluses • Strong coding experience, particularly in Python, including testing, debugging, and working with unfamiliar code Originally posted on Himalayas