

Crossing Hurdles
Data Analyst | $56/hr Remote | Mercor
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Analyst position at Mercor, offering $56/hr for a remote, hourly contract of 10–40 hours/week. Requires Kaggle Grandmaster status, strong data science experience, proficiency in Python and SQL, and excellent communication skills.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
448
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🗓️ - Date
December 5, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Documentation #Data Analysis #AI (Artificial Intelligence) #NumPy #Data Science #Libraries #Pandas #ML (Machine Learning) #Storytelling #SQL (Structured Query Language) #Python #Datasets #Data Storytelling
Role description
At Crossing Hurdles, we work as a referral partner. We refer candidates to Mercor that collaborates with the world’s leading AI research labs to build and train cutting-edge AI models.
Organization: Mercor
Position: Data Scientist (Kaggle Grandmaster)
Referral Partner: Crossing Hurdles
Type: Hourly Contract
Compensation: $56/hour
Location: Remote
Commitment: 10–40 hours/week
Role Responsibilities (Training support will be provided)
• Analyze large, complex datasets to identify patterns and generate actionable insights.
• Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types.
• Design and implement rigorous experiment frameworks and validation strategies.
• Automate workflows, feature pipelines, and reproducible research environments.
• Conduct exploratory data analysis, hypothesis testing, and interpret modeling outcomes.
• Collaborate with ML engineers and research teams to productionize models at scale.
• Present findings through clear documentation, dashboards, and reports.
Requirements
• Kaggle Competitions Grandmaster or equivalent achievement (multiple medals or top-tier rankings).
• Strong experience in data science, analytics, or ML-driven research.
• Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn.
• Solid knowledge of experiment design, causal inference, and statistical modeling.
• Familiarity with SQL, distributed data systems, and experiment tracking tools.
• Excellent communication and data storytelling skills.
Application Process (Takes 20 min)
1. Upload resume
1. AI interview based on your resume (15 min)
1. Submit form
At Crossing Hurdles, we work as a referral partner. We refer candidates to Mercor that collaborates with the world’s leading AI research labs to build and train cutting-edge AI models.
Organization: Mercor
Position: Data Scientist (Kaggle Grandmaster)
Referral Partner: Crossing Hurdles
Type: Hourly Contract
Compensation: $56/hour
Location: Remote
Commitment: 10–40 hours/week
Role Responsibilities (Training support will be provided)
• Analyze large, complex datasets to identify patterns and generate actionable insights.
• Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types.
• Design and implement rigorous experiment frameworks and validation strategies.
• Automate workflows, feature pipelines, and reproducible research environments.
• Conduct exploratory data analysis, hypothesis testing, and interpret modeling outcomes.
• Collaborate with ML engineers and research teams to productionize models at scale.
• Present findings through clear documentation, dashboards, and reports.
Requirements
• Kaggle Competitions Grandmaster or equivalent achievement (multiple medals or top-tier rankings).
• Strong experience in data science, analytics, or ML-driven research.
• Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn.
• Solid knowledge of experiment design, causal inference, and statistical modeling.
• Familiarity with SQL, distributed data systems, and experiment tracking tools.
• Excellent communication and data storytelling skills.
Application Process (Takes 20 min)
1. Upload resume
1. AI interview based on your resume (15 min)
1. Submit form






