Data Scientist | Work From Home

Mercor; Remote; EUR 80.000 - 100.000; Teilzeit

Zusammenfassung

A pioneering AI company is looking for an AI Task Evaluation & Statistical Analysis Specialist. This remote role involves conducting statistical failure analysis of AI agent performances and making recommendations for task improvements. Ideal candidates will have expertise in statistics, data analysis, and proficiency in Python or R. This position is crucial for enhancing AI model performance within the finance domain.

Qualifikationen

• Strong foundation in statistical analysis, hypothesis testing, and pattern recognition.
• Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis.
• Experience with exploratory data analysis and creating actionable insights from complex datasets.
• Understanding of LLM evaluation methods and quality metrics.
• Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL.

Aufgaben

• Conduct comprehensive statistical failure analysis to identify patterns in AI agent failures.
• Perform root cause analysis to determine issues related to task design or agent limitations.
• Analyze performance variations across finance sub-domains and task categories.
• Create dashboards and reports to highlight failure clusters and improvement opportunities.
• Recommend improvements based on statistical findings.
• Present insights to data labeling experts and technical teams.

Kenntnisse

Statistical Expertise

Programming in Python or R

Data Analysis

AI/ML Familiarity

Excel and data visualization tools

SQL

Jobbeschreibung

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position

AI Task Evaluation & Statistical Analysis Specialist

Type

Contract

Compensation

$100–$120/hour

Location

Remote

Role Responsibilities

• Conduct comprehensive statistical failure analysis to identify patterns in AI agent failures across task components such as prompts, rubrics, and templates.
• Perform root cause analysis to determine if failures are due to task design, rubric clarity, file complexity, or agent limitations.
• Analyze performance variations across finance sub-domains, file types, and task categories to enhance understanding of AI model performance.
• Create dashboards and reports to highlight failure clusters, edge cases, and improvement opportunities.
• Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings.
• Present insights to data labeling experts and technical teams to foster collaboration and drive improvements.

Qualifications

Must-Have

• 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), and SQL.

Preferred

• 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.

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
• For any help or support, reach out to: [e-mail]

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.