[Remote] Competitive Data Scientist (Kaggle)

Note: The job is a remote job and is open to candidates in USA. An unnamed client is seeking a Competitive Data Scientist (Kaggle) to design rigorous data science and machine learning tasks for evaluating AI-generated solutions. The role includes building reproducible environments, implementing reference solutions, developing evaluation frameworks, and analyzing AI agent performance.

Responsibilities

• Task Development: Design challenging data science, machine learning, and mathematical modeling tasks based on real-world problems and competitive programming experience
• Environment Setup: Build reproducible execution environments, prepare datasets, configure dependencies, and ensure consistent task execution
• Reference Solutions: Implement accurate, efficient, and verifiable reference solutions for each task
• Testing and Evaluation: Develop automated tests, validation criteria, and evaluation frameworks that distinguish correct solutions from incomplete, inefficient, or flawed implementations
• AI Agent Evaluation: Run AI coding agents against designed tasks, analyze their performance, investigate failure patterns, and refine task specifications based on observed results
• Debugging and Quality Assurance: Identify implementation bugs, incorrect assumptions, data leakage, methodological weaknesses, and other issues that compromise solution quality
• Technical Documentation: Clearly document problem statements, expected outputs, solution methodologies, dependencies, and verification procedures
• Continuous Improvement: Improve task complexity, reproducibility, and evaluation reliability through iterative testing and experimentation

Skills

• Strong expertise in data science, machine learning, statistical modeling, and applied mathematics
• Demonstrated experience participating in data science and machine learning competitions, such as Kaggle, DrivenData, or similar platforms
• Demonstrated experience in data science, machine learning, quantitative modeling, applied mathematics, or a related technical field
• Participation in competitive data science or machine learning platforms, such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench
• Strong analytical reasoning and the ability to break down complex problems into structured, testable solutions
• Practical programming skills sufficient to independently implement, test, debug, and validate technical solutions
• Understanding of statistical methods, predictive modeling, data preprocessing, feature engineering, and model evaluation
• Ability to identify data leakage, overfitting, flawed assumptions, and methodological errors
• Experience evaluating model performance and validating results against reliable benchmarks
• Strong attention to detail and the ability to communicate technical reasoning clearly
• Competitive Data Science
• Kaggle Competitions
• Machine Learning
• Python Programming
• Statistical Analysis and Mathematical Reasoning
• Data Modeling and Model Evaluation
• Testing, Debugging, and Solution Validation
• Experience with DrivenData, Zindi, AIcrowd, Numerai, or similar competition platforms
• Strong Python development skills, including working with unfamiliar codebases
• Experience with pandas, NumPy, scikit-learn, PyTorch, or TensorFlow
• Knowledge of automated testing, reproducible environments, and dependency management
• Experience developing evaluation benchmarks and automated grading systems
• Familiarity with AI coding agents, LLM-based development tools, and agent evaluation
• Experience in quantitative research, optimization, feature engineering, and advanced statistical modeling

Benefits

• Global, fully remote
• Flexible schedule — choose your preferred working hours and days, including weekends

Company Overview