Data Scientist / Data Science Specialist ( Part-Time) $60 – $100/hr Remote India

Data Science Experts

Hourly contract · Remote · $60 –$100 per hour

Role Overview

Contribute to a high-impact AI research initiative focused on advancing exploratory data analysis (EDA) capabilities in large language models. The role involves evaluating AI-generated analysis, designing structured rubrics, and producing gold-standard responses including statistical insights, visualizations, and executable Python code.

Key Responsibilities

• Review AI-generated exploratory data analysis outputs for accuracy and quality.
• Apply statistical methods and modeling techniques to validate insights across structured and unstructured datasets.
• Design prompts and detailed evaluation rubrics for fine-grained performance assessment.
• Deliver gold-standard examples, including clear visualizations, explanatory text, and Python notebooks.
• Translate data-driven reasoning and decision-making into clear, gradable criteria for AI training.

Ideal Qualifications

• Bachelor’s, Master’s, or PhD in Data Science, Computer Science, Statistics, Mathematics, or related field, OR 2+ years of industry experience in a data science role.
• Proficiency with Python and core data science libraries (pandas, numpy, scikit-learn).
• Strong foundation in statistical modeling, data analysis, and machine learning principles.
• Ability to identify meaningful patterns, trends, and associations within complex datasets.
• Excellent analytical writing skills with the ability to communicate insights clearly and concisely.

Project Details

• Start: Immediate.
• Duration: 5–6 weeks.
• Commitment: Part-time, 10–20 hours/week (flexible).
• Schedule: Fully remote and asynchronous.

Compensation & Contract

• $60–$100/hour USD, depending on experience.
• Top performers may receive bonus incentives of $20–$50/hour.
• Independent contractor engagement.
• Weekly payments via Stripe Connect.

Application Process

1. Submit resume.
2. Complete a short technical interview (25 minutes) including project-based conceptual questions and a Google Co-Lab data analysis exercise.