Open to opportunities

Alessandro User

@alessandrouser4

Message

I build Python algorithmic trading systems from market data research through live execution.

Zimbabwe

Message

What I'm looking for

I'm looking to build and improve algorithmic trading systems, from market-data infrastructure and research through robust live execution, ideally in quantitative trading or data-driven financial markets.

I've built and run automated trading systems in Python for crypto and equity markets since September 2023, covering exchange connectivity, market data, backtesting, and live execution.

My live systems connect to Binance, Bybit, and Alpaca through REST and WebSocket APIs, handling orders, reconnections, and position tracking. I developed a modular backtesting and live-trading engine with transaction costs, dynamic position sizing, and drawdown constraints, alongside ETL pipelines for crypto, FX, equities, and derivatives data.

Previously at SORINT.tek, I built market data infrastructure for a trading desk, developed Spark-based suspicious-transaction detection pipelines, and delivered machine learning systems for anomaly detection, computer vision, and sensor analytics.

At the European Central Bank, I prepared balance-sheet datasets supporting banking supervision dashboards. I hold an MSc in Statistical Sciences and bring hands-on experience in time series analysis, cointegration, machine learning, and quantitative finance.

Experience

Work history, roles, and key accomplishments

Current

Quantitative Developer and Data Scientist

Current

Freelance

Sep 2023 - Present (2 years 11 months)

Designed and ran automated trading bots in Python, connecting to Binance, Bybit, and Alpaca via REST and WebSocket APIs. Developed a modular backtesting and live-trading engine with transaction costs, dynamic position sizing, and drawdown constraints.

Python Bybit API Alpaca API REST WebSockets Trading Systems ETL Parquet Convolutional Neural Networks Cointegration

Data Scientist and Data Analyst

SORINT.tek

Sep 2020 - Aug 2023 (2 years 11 months)

Used Spark and PySpark to extract suspicious transactions from a bank database and wrote results to HDFS. Set up machine learning jobs for anomaly detection with Kibana dashboards, and trained CNN and RNN models on AWS for EEG stress analysis.

Spark PySpark HDFS Machine Learning Anomaly Detection Kibana CNN RNN AWS Detectron2 Transfer Learning

Data Analyst

European Central Bank

Sep 2019 - Aug 2020 (11 months)

Pulled balance sheet data on major European banks from an internal database, cleaned it in SAS, and prepared datasets for Tableau dashboards used in supervision, following Single Supervisory Mechanism rules.

SAS Tableau Data Cleaning Single Supervisory Mechanism