

Great Value Hiring
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist position for a contract length of "unknown" at a pay rate of $100-$120/hr. Key skills include statistical analysis, Python or R proficiency, and AI/ML familiarity, with a preference for finance sector experience and multi-dimensional failure analysis expertise.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
960
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🗓️ - Date
November 7, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#AI (Artificial Intelligence) #ML (Machine Learning) #Looker #Datasets #Matplotlib #Python #Programming #Tableau #Model Evaluation #SciPy #R #Data Analysis #Visualization #Pandas #Data Science #Quality Assurance
Role description
Data Scientist [$100-$120/hr]
AI Task Evaluation & Statistical Analysis Specialist
As referral partner, we are posting to seek a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.).
Key Responsibilities
• Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags)
• Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations
• Dimension Analysis: Analyze performance variations across finance sub-domains, file types, and task categories
• Reporting & Visualization: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities
• Quality Framework: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings
• Stakeholder Communication: Present insights to data labeling experts and technical teams
Required Qualifications
• Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition
• Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis
• Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets
• AI/ML Familiarity: Understanding of LLM evaluation methods and quality metrics
• Tools: Comfortable working with Excel, data visualization tools (Tableau/Looker), andSQL
Preferred Qualifications
• Experience with AI/ML model evaluation or quality assurance
• Background in finance or willingness to learn finance domain concepts
• Experience with multi-dimensional failure analysis
• Familiarity with benchmark datasets and evaluation frameworks
• 2-4 years of relevant experience
Data Scientist [$100-$120/hr]
AI Task Evaluation & Statistical Analysis Specialist
As referral partner, we are posting to seek a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.).
Key Responsibilities
• Statistical Failure Analysis: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags)
• Root Cause Analysis: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations
• Dimension Analysis: Analyze performance variations across finance sub-domains, file types, and task categories
• Reporting & Visualization: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities
• Quality Framework: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings
• Stakeholder Communication: Present insights to data labeling experts and technical teams
Required Qualifications
• Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition
• Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis
• Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets
• AI/ML Familiarity: Understanding of LLM evaluation methods and quality metrics
• Tools: Comfortable working with Excel, data visualization tools (Tableau/Looker), andSQL
Preferred Qualifications
• Experience with AI/ML model evaluation or quality assurance
• Background in finance or willingness to learn finance domain concepts
• Experience with multi-dimensional failure analysis
• Familiarity with benchmark datasets and evaluation frameworks
• 2-4 years of relevant experience






