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# Data Scientist

- **Company:** ONE STOP COLLECTIBLE CORP
- **Location:** New York, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Data Infrastructure, Python (Programming Language), NumPy, Blockchain, Tensorflow, SQL Databases, Pytorch, Snowflake, Pandas, Build Management, Scikit Learn, Web3.js, Amazon Redshift, Databricks
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/data-scientist-funxyz-decircle-8349782

## About the Role

This role is perfect for someone who thrives in fast-paced, ownership-driven environments, loves solving open-ended problems, and is excited about the potential of blockchain data., * Proficiency in Python and SQL (5+ years)

 * Strong background in statistical analysis, experimentation, and causal inference
 * Familiar with analyzing end-user behavior for optimization (A/B testing, conversion rates, etc.)
 * Skilled in modern data platforms (Redshift, Snowflake, Databricks, etc.) and orchestration/transformation tools (dbt or similar)
 * Deep curiosity about crypto, DeFi, on-chain data, and Web3 infrastructure

Nice To Have

 * Experience analyzing large-scale transaction or financial datasets
 * Hands-on experience with ML/AI libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow)
 * Familiarity with market dynamics (spreads, slippage, liquidity, etc.)
 * A track record of thriving in ownership-heavy, fast-moving environments
 * A problem-solving approach that blends rigor, creativity, and first-principles thinking

## Description

* Design and build scalable data models to analyze transaction flows and user behavior
 * Support the optimization of data transformations, pipelines, and workflows
 * Work directly with the CFO to provide insights on the business' performance
 * Maintain data quality, observability, and reproducibility across analytical systems
 * Partner with engineers and product teams to deliver actionable, production-grade insights
 * Run experiments, apply causal inference, and drive evidence-based product decisions
 * Translate complex data into clear stories for both technical and non-technical stakeholders


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