Available for opportunities

Hi, I'm Kyriakos Christou

Blockchain Research Analyst

I'm a Blockchain Research Analyst passionate about data-driven blockchain ecosystems. My work focuses on building analytical pipelines, studying tokenomics models, and uncovering insights that support ecosystem growth and transparency.

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Featured Projects

Showcasing my latest work

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Chain Pulse

data-pipeline blockchain ETL

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Economic Model Simulation (PoW)

data-science blockchain modeling

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Error Clustering and Faucet Analysis

data-science blockchain user-ops analytics visualization

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Chain Pulse

End-to-end data engineering pipeline that collects, processes, and reports blockchain metrics across multiple chains.

data-pipeline blockchain ETL automation aws

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Economic Model Simulation (PoW)

A data science simulation modeling agent behavior in a blockchain network under Proof-of-Work consensus.

data-science blockchain modeling simulation economics

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Error Clustering and Faucet Analysis

Blockchain data analysis project extracting and analyzing Account Abstraction testnet data with error clustering and faucet bot detection.

data-science blockchain user-ops analytics visualization

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LP Reward Model App

Interactive Streamlit app to simulate LP reward programs: quadratic time-unlock APR for lockers, optional early-unlock penalty, flexible LP multipliers, and staged timelines with interactive charts.

app defi streamlit analytics tokenomics

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Ethereum Gas Fee Analysis & Forecasting

Exploratory analysis of Ethereum transaction fees and gas prices with hourly/weekday patterns, wallet vs network comparisons, and an ARIMA model for short-term forecasts.

ethereum time-series arima analytics

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Light Banking System App

Lightweight Flask banking demo that integrates with Striga’s sandbox: signed API calls (HMAC+MD5), live EUR & crypto wallets, deposit details (IBAN/BIC or crypto address), cards and transactions, and real-time UI updates via webhooks & SSE. Outbound actions (SEPA send, crypto withdraw) are safe local simulations that drive realistic activity.

flask striga webhooks sse demo-app

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Blockchain Insights Pipeline

Production-grade ETL and analytics pipeline for Ethereum on-chain data using Airflow, PostgreSQL, and dbt with live ingestion, gap repair, and automated transformations.

data-engineering blockchain airflow dbt etl postgresql docker

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Chain Pulse

End-to-end data engineering pipeline that collects, processes, and reports blockchain metrics across multiple chains. The system automates daily comparisons, enabling clear visibility into network performance and economic trends.

Key Highlights

Three-stage Lambda pipeline: Collector, Processor, Reporter
Dual-mode architecture (local or AWS S3)
Automated daily Markdown reports with visual charts
Compares data across consecutive days for insights

Tech Stack

Python Pandas Matplotlib AWS Lambda EventBridge S3

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Economic Model Simulation (PoW)

A data science simulation project that models the behavior of agents in a blockchain network under a Proof-of-Work consensus. The goal was to predict how different parameters affect agent activity, token circulation, and macroeconomic indicators using system dynamics and visualization.

Key Highlights

Built a modular simulation using cadCAD
Modeled agent interactions (users, developers, miners, bundlers)
Calculated and visualized metrics like APY, token velocity, and inflation rate
Analyzed system equilibrium through parameter tuning and visual heatmaps

Tech Stack

Python cadCAD Matplotlib Pandas NumPy Data Visualization

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Error Clustering and Faucet Analysis

A comprehensive blockchain data analysis project focused on extracting and analyzing data from an Account Abstraction (AA) testnet. The project performs error clustering across various components and includes faucet analysis to detect potential bot accounts based on sender activity patterns.

Key Highlights

Data collection at block and UserOperation event level from AA testnet
Clustering of recurring UserOperation errors across different system components
Visualization of error frequency and distribution patterns using multiple libraries
Faucet click pattern analysis to identify and flag potential bot accounts

Tech Stack

Python Pandas NumPy Web3.py Matplotlib Seaborn Plotly Aiohttp Jupyter

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LP Reward Model App

A Streamlit application for modeling LP rewards in DeFi. Configure stage timelines, apply quadratic time-unlock APR for lockers (with optional early-unlock penalty), and scale flexible-liquidity rewards via bucket multipliers. Explore outcomes with interactive tables and Plotly charts.

Key Highlights

Configurable staged timeline for LP incentives
Quadratic APR unlock for lockers; optional early-unlock penalty
Flexible LP rewards via bucket multipliers and fixed stage shares
Interactive tables and Plotly charts for APR, liquidity, and combined rewards

Tech Stack

Streamlit Python Pandas Plotly Jupyter

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Ethereum Gas Fee Analysis & Forecasting

Exploratory analysis of Ethereum transaction fees and gas prices over time. I examine hourly and weekday patterns, compare wallet-level fees to network averages, and use ARIMA to forecast short-term movements.

Key Highlights

EDA for hour-of-day and weekday/weekend fee patterns
Wallet-level vs network-average comparisons
Stationarity checks and differencing before modeling
ARIMA forecasts with intervals and validation

Tech Stack

Python Pandas Matplotlib Seaborn Statsmodels SciPy Jupyter Bokeh Plotting Etherscan

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Light Banking System App

A lightweight banking demo built in Flask that connects to Striga’s sandbox to show how a real consumer app could look and behave—without touching real money. It signs every request like production (HMAC + MD5), pulls live data for the active user (KYC status, EUR & crypto wallets, balances, IBAN/BIC or deposit addresses, cards and transactions), and updates the browser in real time through webhooks and Server-Sent Events. Outbound actions are safe, local simulations (SEPA send & crypto withdraw) that produce realistic activity so totals and histories refresh exactly as they would in production.

Key Highlights

Production-style request signing (HMAC + MD5) to Striga’s sandbox APIs
Live EUR accounts & crypto wallets with deposit details (IBAN/BIC or blockchain address)
Real-time UI updates via webhooks → SSE for KYC, transactions, and card status
Safe demo flows: simulated SEPA send and crypto withdrawal that drive live updates
Admin screen to register users and “Set Active” (impersonation) for demos

Tech Stack

Flask Python Striga Webhooks SSE HTML CSS

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Ethereum Insights Pipeline

Fully automated ETL and analytics pipeline that ingests live Ethereum blockchain data and market prices, stores raw data in PostgreSQL, transforms it with dbt, and ensures data completeness via scheduled repair jobs orchestrated with Apache Airflow.

Key Highlights

Incremental ingestion of Ethereum blocks and transactions
Hourly price data ingestion from Binance
Daily gap repair to ensure full historical coverage
Analytics-ready transformations using dbt
End-to-end orchestration with Apache Airflow DAGs
Fully reproducible local setup using Docker

Tech Stack

Python Apache Airflow PostgreSQL dbt Docker Etherscan API Binance API DBeaver

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About Me

Learn more about my background and expertise

I'm a Blockchain Research Analyst passionate about data-driven blockchain ecosystems. My work focuses on building analytical pipelines, studying tokenomics models, and uncovering insights that support ecosystem growth and transparency.

Get in Touch

Email

kyris1926@gmail.com

GitHub

View my repositories

Connect professionally

Location

Cyprus

Get in Touch

Have a project in mind or want to collaborate? Send me a message!