Competitive Data Scientist

Job summary

Build reproducible task environments, prepare data and dependencies, implement reference solutions, and create tests that distinguish correct solutions from flawed ones. Evaluate coding agents, investigate failures, refine tasks, identify correctness issues, and document requirements, reasoning, and verification steps.

Job details

Competitive Data Scientist [$60 - $120/hour] Role Responsibilities 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 Good Candidature 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. Nice to Have Strong coding experience, particularly in Python, including testing, debugging, and working with unfamiliar code

What you’ll do

Build reproducible task environments, prepare data and dependencies, implement reference solutions, and create tests that distinguish correct solutions from flawed ones. Evaluate coding agents, investigate failures, refine tasks, identify correctness issues, and document requirements, reasoning, and verification steps.

Requirements

Candidates should have demonstrated experience in data science, machine learning, quantitative modeling, or relevant research competitions, along with strong problem-solving ability and practical programming skills. Python experience, including testing, debugging, and working with unfamiliar code, is an advantage.

Listed skills

• Problem solving · Preferred
• Machine learning · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Science
• Machine Learning
• Quantitative Modeling
• Python Programming
• Problem-Solving
• Reproducible Environments
• Data Preparation
• Testing
• Evaluation Criteria
• Debugging
• Coding Agents
• Data Leakage Detection
• Solution Verification
• Research Competitions

Job areas

• Data & Analytics
• Technology
• Software
• Science & Research

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