

Alignerr
Data Scientist – AI Training & Evaluation
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist – AI Training & Evaluation, offering a remote hourly contract for 10–40 hours/week at $25–$40/hour. Key skills include statistics, machine learning, Python, R, and SQL. A degree in a related field is required.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
320
-
🗓️ - Date
April 3, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
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📄 - Contract
W2 Contractor
-
🔒 - Security
Unknown
-
📍 - Location detailed
New York, NY
-
🧠 - Skills detailed
#TensorFlow #Model Evaluation #Data Science #NLP (Natural Language Processing) #Computer Science #PyTorch #Mathematics #Deep Learning #AI (Artificial Intelligence) #R #SQL (Structured Query Language) #ML (Machine Learning) #A/B Testing #Python #Visualization #Data Analysis #Statistics #Data Wrangling
Role description
About The Role
We're looking for data scientists based in the New York metro area to help train, evaluate, and improve next-generation AI systems. You'll leverage your expertise in statistics, machine learning, and data analysis to assess AI model outputs, design evaluation frameworks, and ensure AI systems deliver accurate, reliable results.
• Organization: Alignerr
• Type: Hourly Contract
• Compensation: $25–$40 /hour
• Location: Remote (US-based)
• Commitment: 10–40 hours/week
What You'll Do
• Evaluate AI model outputs for accuracy, reasoning quality, and statistical soundness
• Design and apply data-driven evaluation criteria and scoring rubrics
• Analyze patterns in AI-generated responses to identify systematic errors or biases
• Create high-quality training data including prompts, solutions, and annotations in your areas of expertise
• Provide structured, detailed feedback to improve model performance across data science and analytical tasks
• Review AI-generated code, visualizations, and statistical analyses for correctness
• Work independently and asynchronously on your own schedule
Who You Are
• Based in the United States
• Degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field (MS or PhD preferred)
• Strong foundation in statistics, probability, and machine learning concepts
• Proficiency in Python, R, SQL, or similar data analysis tools
• Experience with data wrangling, exploratory data analysis, and model evaluation
• Excellent analytical thinking and attention to detail
• Clear written communication — able to explain complex technical concepts simply
• Self-motivated and comfortable working independently
Nice to Have
• Experience with deep learning frameworks (PyTorch, TensorFlow)
• Familiarity with NLP, LLMs, or AI evaluation workflows
• Published research or industry experience in applied machine learning
• Background in A/B testing, causal inference, or experimental design
Why Join Us
• Work on cutting-edge AI projects shaping the future of technology
• Collaborate with top research labs and AI teams globally
• Freelance perks: full autonomy, flexible scheduling, and remote-first culture
• Gain deep exposure to how state-of-the-art LLMs are trained and evaluated
• Potential for ongoing work and long-term contract extension
• Be part of a growing community of expert contributors making AI smarter
Application Process (Takes 10–15 min)
• Submit your resume
• Complete a short screening
• Project matching and onboarding
PS: Our team reviews applications daily. Please complete your application steps to be considered for this opportunity.
About The Role
We're looking for data scientists based in the New York metro area to help train, evaluate, and improve next-generation AI systems. You'll leverage your expertise in statistics, machine learning, and data analysis to assess AI model outputs, design evaluation frameworks, and ensure AI systems deliver accurate, reliable results.
• Organization: Alignerr
• Type: Hourly Contract
• Compensation: $25–$40 /hour
• Location: Remote (US-based)
• Commitment: 10–40 hours/week
What You'll Do
• Evaluate AI model outputs for accuracy, reasoning quality, and statistical soundness
• Design and apply data-driven evaluation criteria and scoring rubrics
• Analyze patterns in AI-generated responses to identify systematic errors or biases
• Create high-quality training data including prompts, solutions, and annotations in your areas of expertise
• Provide structured, detailed feedback to improve model performance across data science and analytical tasks
• Review AI-generated code, visualizations, and statistical analyses for correctness
• Work independently and asynchronously on your own schedule
Who You Are
• Based in the United States
• Degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field (MS or PhD preferred)
• Strong foundation in statistics, probability, and machine learning concepts
• Proficiency in Python, R, SQL, or similar data analysis tools
• Experience with data wrangling, exploratory data analysis, and model evaluation
• Excellent analytical thinking and attention to detail
• Clear written communication — able to explain complex technical concepts simply
• Self-motivated and comfortable working independently
Nice to Have
• Experience with deep learning frameworks (PyTorch, TensorFlow)
• Familiarity with NLP, LLMs, or AI evaluation workflows
• Published research or industry experience in applied machine learning
• Background in A/B testing, causal inference, or experimental design
Why Join Us
• Work on cutting-edge AI projects shaping the future of technology
• Collaborate with top research labs and AI teams globally
• Freelance perks: full autonomy, flexible scheduling, and remote-first culture
• Gain deep exposure to how state-of-the-art LLMs are trained and evaluated
• Potential for ongoing work and long-term contract extension
• Be part of a growing community of expert contributors making AI smarter
Application Process (Takes 10–15 min)
• Submit your resume
• Complete a short screening
• Project matching and onboarding
PS: Our team reviews applications daily. Please complete your application steps to be considered for this opportunity.






