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Outlier is a platform owned and operated by Scale AI and believes AI can only perform as well as the data it’s trained on. That’s why we work with contributors from all over the world, who help improve AI models by providing expert human feedback. This data has led to AI advancements for the world's leading AI labs and large language model builders. \n We’ve built a best-in-class remote work platform for our freelance contributors to provide valuable, specialized skills, and we in turn strive to provide them with a positive experience based on our core pillars of reliability, transparency, and flexibility. \nWhat you will be doing\n\n • Create a grading rubric on what a good answer would be.\n, • Write the correct answer that scores 100% on the rubric.\n, • Provide clear, constructive feedback to improve AI-generated responses.\n\nWhat we’re looking for\n\n, • PhD or Master's Degree in Finance or a related field. Can be currently enrolled.\n, • Deep subject matter expertise with the ability to create complex, graduate-level problems that challenge AI reasoning.\n, • Strong analytical and problem-solving skills, with experience in crafting rigorous, high-quality questions and solutions.\n, • Attention to detail to accurately assess AI capabilities and evaluate peer submissions.\n, • Fluency/High proficiency in English.\n\n

Overview Outlier is a platform owned and operated by Scale AI and believes AI can only perform as well as the data it’s trained on. That’s why we work with contributors from all over the world, who help improve AI models by providing expert human feedback. This data has led to AI advancements for the world's leading AI labs and large language model builders. \n We’ve built a best-in-class remote work platform for our freelance contributors to provide valuable, specialized skills, and we in turn strive to provide them with a positive experience based on our core pillars of reliability, transparency, and flexibility. \n What you will be doing • We are looking for proficient accounting experts to teach AI how to interpret and solve complex reasoning problems., • Create a challenging prompt that the model fails to answer correctly., • Create a grading rubric on what a good answer would be., • PhD or Master's Degree in Accounting or a related field. Can be currently enrolled., • Deep subject matter expertise with the ability to create complex, graduate-level problems that challenge AI reasoning., • Strong analytical and problem-solving skills, with experience in crafting rigorous, high-quality questions and solutions., • Attention to detail to accurately assess AI capabilities and evaluate peer submissions.

Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking 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), and SQL ## 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

Competitive pay - As a Data Verification Analyst at Foundation AI, you will: Process, segregate, review, and validate data provided in various formats according to changing process requirements; Prepare, compile, and organize documents for data capture, ensuring accuracy and completeness; Log and ve

Job DescriptionData Analysis - AI Training RoleAbout our client Our client is a leading force in advancing safer, smarter AI technology. Their work has been featured in Forbes, The New York Times, and other major outlets for pioneering high-quality, human-verified data that powers today’s top AI systems. They have built a global community of expert contributors and have paid more than $500 million to professionals all over the world who help train, test, and improve next-generation AI models. Why join this team? • Earn up to $50/hr, paid weekly., • Payments via PayPal or AirTM., • No contracts, no 9-to-5 - you control your schedule., • Most experts work 5-10 hours/week, with the option to work up to 40 hours from home., • Join a global community of experts contributing to advanced AI tools., • Free access to the Model Playground to interact with leading LLMs.Requirements, • Bachelor’s degree or higher in a quantitative, technical, or business discipline (e.g., Statistics, Mathematics, Data Science, Operations Research, Computer Science, Engineering, Economics, Finance, or similar)., • 2+ years of experience in an analyst, consultant, or research role involving quantitative analysis, modeling, or forecasting., • Demonstrated experience working with datasets end-to-end: sourcing, cleaning, analyzing, and deriving insights., • Proficiency with data analysis tools such as Python, R, SQL, or similar, and familiarity with visualization methods., • Strong problem-solving skills, attention to detail, and ability to clearly explain results to non-technical audiences.What you’ll do, • Support the training of generative AI models by applying advanced analytical skills., • Find and source open datasets relevant to business and research needs., • Clean, transform, and prepare data for analysis and modeling., • Build statistical or forecasting models to extract meaningful insights.

Driving conversion data mapping activities, including defining the conversion approach/populations, determining the correct source data attributes, and analyzing source data to uncover potential data issues that may impact the conversion. Additionally, the Worker should have development experience,

Partner with data stewards, data engineering, and BI teams to align data sources with enterprise data models, and recommend improvements to data architecture. As part of the growing Data Governance team, you will assist with monitoring data quality, cataloging critical data elements, and promoting d

Acquire data from various sources, perform data validation, and maintain organized and error-free databases. Develop data models, define data requirements, and document metadata and supporting structures. Job title: Senior Data Analyst - Environmental Epidemiology.

Support senior analysts and business stakeholders in data-driven decision-making. Document data processes and maintain data accuracy across all reporting systems. Knowledge of basic statistics and data visualization principles.

The Business Data Analyst will primarily focus on analyzing existing business requirements to understand current functionalities, data flows, and pain points. Experience creating and maintaining data-related documentation including data dictionaries, business requirement documents, and data mapping

Take the next step in your career as our new Netflix Data Analyst to perform responsibilities as a Data Analyst.

Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises related to finance management.

Take the next step in your career as our new Netflix Data Analyst to perform responsibilities as a Data Analyst.

Support senior analysts and business stakeholders in data-driven decision-making. Document data processes and maintain data accuracy across all reporting systems. Ability to work independently in a fast-paced, data-driven environment.

Bring your energy to the role of Netflix Data Analyst to adapt to shifting priorities and business needs, work collaboratively across teams and departments, and provide excellent service to customers and team members.

The Business Data Analyst will primarily focus on analyzing existing business requirements to understand current functionalities, data flows, and pain points. Experience creating and maintaining data-related documentation including data dictionaries, business requirement documents, and data mapping

Partner with data stewards, data engineering, and BI teams to align data sources with enterprise data models, and recommend improvements to data architecture. This is an excellent opportunity for an analyst with foundational experience in data governance or data management who is eager to contribute

Developing SQLs/Alteryx Workflows to identify quality/consistency issues within the PeopleSoft source data - and recommending methods to cleanse the data, repair the root cause of the data issue, and/or adjust the conversion rules for migrating the data. Additionally, the Worker should have developm

Develop data models, define data requirements, and document metadata and supporting structures. Acquire data from various sources, perform data validation, and maintain organized and error-free databases. Job title: Senior Data Analyst - Environmental Epidemiology.