Competitive Data Scientist, Kaggle

This is a fully remote position, open to applicants in India, +1 more country.

📋 Description

• Create intricate data science, machine learning, and mathematical modeling tasks rooted in real-world challenges and competitive programming expertise.

• Establish reproducible execution environments, curate datasets, set up dependencies, and guarantee uniformity in task execution.

• Develop precise, efficient, and verifiable reference solutions.

• Create automated tests, validation standards, and evaluation frameworks to differentiate correct solutions from incomplete, inefficient, or erroneous implementations.

• Execute AI coding agents on designed tasks, assess performance, examine failure patterns, and refine task specifications accordingly.

• Detect implementation bugs, erroneous assumptions, data leakage, methodological flaws, and other factors that may impact solution quality.

• Document problem statements, anticipated outputs, solution methodologies, dependencies, and verification procedures.

• Enhance task complexity, reproducibility, and evaluation reliability through a process of iterative testing and experimentation.

⛳️ Requirements

• Proven experience in data science, machine learning, quantitative modeling, applied mathematics, or a related technical discipline.

• Involvement in competitive data science or machine learning platforms such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench.

• Strong analytical reasoning skills with the capability to decompose complex problems into structured, testable solutions.

• Practical programming expertise adequate to independently implement, test, debug, and validate technical solutions.

• Familiarity with statistical methods, predictive modeling, data preprocessing, feature engineering, and model evaluation.

• Capability to identify data leakage, overfitting, flawed assumptions, and methodological inaccuracies.

• Experience in evaluating model performance and corroborating results against reliable benchmarks.

• Keen attention to detail and proficiency in articulating technical reasoning clearly.

• Background in competitive data science.

• Participation in Kaggle competitions.

• Proficiency in machine learning.

• Expertise in Python programming.

• Skills in statistical analysis and mathematical reasoning.

• Knowledge of data modeling and model evaluation.

• Experience in testing, debugging, and validating solutions.

• Familiarity with platforms like DrivenData, Zindi, AIcrowd, Numerai, or similar competition venues.

• Advanced Python development skills, including experience with unfamiliar codebases.

• Proficient with libraries such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.

• Understanding of automated testing, reproducible environments, and dependency management.

• Experience in developing evaluation benchmarks and automated grading systems.

• Acquaintance with AI coding agents, LLM-based development tools, and agent evaluation.

• Background in quantitative research, optimization, feature engineering, and advanced statistical modeling.

🏝️ Benefits

• Fully remote work arrangement.

• Flexible schedule — select preferred working hours and days, including weekends.

• Contractor schedule of approximately 15 hours per week.