Blockchain Data Analyst with AI & Backtesting Expertise (Crypto Trading Focus)
Budget: $30 – $250 USD
About the Role:
We are looking for a highly skilled Blockchain Data Analyst with deep experience in analyzing large-scale on-chain data, running backtesting scenarios, and utilizing AI tools to derive actionable trading insights. You will work closely with our trading and product development teams to explore patterns in blockchain data, develop hypotheses, and validate them using historical and real-time data from major blockchain networks.
This is not a generic data analyst role. We need someone who lives and breathes crypto, knows how to extract and interpret wallet-level data, historical price performance and identify market anomalies, and feed structured datasets into AI models (LLMs, ML frameworks, etc.) for predictive and pattern recognition purposes.
Responsibilities:
- Analyze large blockchain datasets (e.g., from Solana, Ethereum, BSC, etc.) to detect patterns in pricing, wallet behavior, trading volumes, token movement, and unusual activity.
- Conduct backtests of trading strategies using historical blockchain data and provide performance metrics and statistical validations.
- Feed curated data into AI systems and collaborate on designing prompts, models, or data pipelines to enhance pattern recognition and decision support.
- Build dashboards, visualizations, and reports to convey insights to traders and strategists in a clear, actionable manner.
Proactively identify trends, arbitrage windows, and high-potential indicators using data-driven analysis.
Work with APIs (e.g., Moralis, Helios, Alchemy, or custom RPC solutions) to access and normalize blockchain data.
Requirements:
- Proven experience in blockchain data analysis, preferably in crypto trading environments.
- Strong knowledge of backtesting methodologies, including Sharpe ratios, drawdowns, and volatility analysis.
- Experience with AI/ML models (e.g., OpenAI, LangChain, Python ML frameworks) and the ability to structure datasets for intelligent pattern recognition.
- Solid understanding of blockchain mechanics (wallets, tokens, DeFi protocols, smart contract interactions).
- Proficiency in tools such as Python, Pandas, NumPy, SQL, Jupyter, Dune, Flipside Crypto, etc.
- Ability to handle noisy, unstructured data and extract signal from noise.
- Excellent communication skills to turn complex data into clear findings and strategic recommendations.
Nice to Have:
- Experience working with Telegram bots or alerting systems based on triggers from data patterns.
- Knowledge of anomaly detection, trend prediction, or chain-agnostic analysis.
- Past work in quantitative crypto hedge funds, crypto exchanges, or blockchain analytics firms.
How to Apply:
Please include:
- A short introduction about your background and relevant experience.
- Examples of past projects (especially involving blockchain analysis, backtesting, or AI-driven conclusions).
- Links to GitHub, publications, dashboards, or tools you’ve developed (if available).
***MUST HAVE: Access to historical token price data
We are looking for a highly skilled Blockchain Data Analyst with deep experience in analyzing large-scale on-chain data, running backtesting scenarios, and utilizing AI tools to derive actionable trading insights. You will work closely with our trading and product development teams to explore patterns in blockchain data, develop hypotheses, and validate them using historical and real-time data from major blockchain networks.
This is not a generic data analyst role. We need someone who lives and breathes crypto, knows how to extract and interpret wallet-level data, historical price performance and identify market anomalies, and feed structured datasets into AI models (LLMs, ML frameworks, etc.) for predictive and pattern recognition purposes.
Responsibilities:
- Analyze large blockchain datasets (e.g., from Solana, Ethereum, BSC, etc.) to detect patterns in pricing, wallet behavior, trading volumes, token movement, and unusual activity.
- Conduct backtests of trading strategies using historical blockchain data and provide performance metrics and statistical validations.
- Feed curated data into AI systems and collaborate on designing prompts, models, or data pipelines to enhance pattern recognition and decision support.
- Build dashboards, visualizations, and reports to convey insights to traders and strategists in a clear, actionable manner.
Proactively identify trends, arbitrage windows, and high-potential indicators using data-driven analysis.
Work with APIs (e.g., Moralis, Helios, Alchemy, or custom RPC solutions) to access and normalize blockchain data.
Requirements:
- Proven experience in blockchain data analysis, preferably in crypto trading environments.
- Strong knowledge of backtesting methodologies, including Sharpe ratios, drawdowns, and volatility analysis.
- Experience with AI/ML models (e.g., OpenAI, LangChain, Python ML frameworks) and the ability to structure datasets for intelligent pattern recognition.
- Solid understanding of blockchain mechanics (wallets, tokens, DeFi protocols, smart contract interactions).
- Proficiency in tools such as Python, Pandas, NumPy, SQL, Jupyter, Dune, Flipside Crypto, etc.
- Ability to handle noisy, unstructured data and extract signal from noise.
- Excellent communication skills to turn complex data into clear findings and strategic recommendations.
Nice to Have:
- Experience working with Telegram bots or alerting systems based on triggers from data patterns.
- Knowledge of anomaly detection, trend prediction, or chain-agnostic analysis.
- Past work in quantitative crypto hedge funds, crypto exchanges, or blockchain analytics firms.
How to Apply:
Please include:
- A short introduction about your background and relevant experience.
- Examples of past projects (especially involving blockchain analysis, backtesting, or AI-driven conclusions).
- Links to GitHub, publications, dashboards, or tools you’ve developed (if available).
***MUST HAVE: Access to historical token price data
Related categories:
Python
Statistics
Data Mining
Statistical Analysis
Data Science
Blockchain
Data Analysis
Backtesting