Competitive Data Scientist, Kaggle

Job not on LinkedIn

🔥 19 minutes ago

🌐 India, United States – Remote

🇮🇳 India – Remote 🇺🇸 United States – Remote

💵 $60 - $120 / hour

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💼 Consulting

👥 HR Tech

☁️ SaaS

Consulting • HR Tech • SaaS

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• Design challenging data science, machine learning, and mathematical modeling tasks based on real-world problems and competitive programming experience • Build reproducible execution environments, prepare datasets, configure dependencies, and ensure consistent task execution • Implement accurate, efficient, and verifiable reference solutions • Develop automated tests, validation criteria, and evaluation frameworks to distinguish correct solutions from incomplete, inefficient, or flawed implementations • Run AI coding agents against designed tasks, analyze performance, investigate failure patterns, and refine task specifications • Identify implementation bugs, incorrect assumptions, data leakage, methodological weaknesses, and other issues affecting solution quality • Document problem statements, expected outputs, solution methodologies, dependencies, and verification procedures • Improve task complexity, reproducibility, and evaluation reliability through iterative testing and experimentation

🎯 Requirements

• 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 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 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

• Fully remote work arrangement • Flexible schedule — choose preferred working hours and days, including weekends • Contractor schedule of approximately 15 hours per week