Олександр

Oleksandr Dovhulia
Quantitative & Data Analyst

Kyiv, Ukraine (Remote) | [відкрити контакти](див. вище в блоці «контактна інформація») | GitHub: OleksanderSS

PROFESSIONAL SUMMARY
Analytical Engineer (M.Eng.) with 5+ years of experience in real-time quantitative analysis, risk management, and statistical modelling. Proficient in Python (Pandas, NumPy) and SQL for exploratory data analysis (EDA), anomaly detection, and data pipeline design. Strong background in applying rigorous failure-mode and quality assurance frameworks to quantitative datasets.
CORE COMPETENCIES
• Data Analysis & Manipulation: Python (Pandas, NumPy), SQL, Time Series Analysis, Feature Engineering.
• Quantitative Risk Management: Probability Assessment, Risk Modelling (Kelly Criterion), Volatility Metrics.
• Engineering & QA: Quality Assurance, Failure Mode Analysis, Data Integrity, Root Cause Identification.
• Visualisation & Tools: Matplotlib, Jupyter Notebooks, Google Colab, Git.
PROFESSIONAL EXPERIENCE
Quantitative Data Analyst (Independent Research) | Sep 2025 – Present

• Architected an end-to-end data pipeline in Python for multi-stage financial time-series forecasting.
• Engineered feature matrices and automated data cleansing pipelines using Pandas and NumPy to filter noise and detect statistical patterns.
• Integrated macroeconomic context indicators to optimise model predictive accuracy and evaluate volatility shifts.
• Built automated visualisation scripts in Matplotlib to audit data distribution, model drift, and historical performance metrics.

Quantitative Markets Analyst | Sports Trading | 2020 – 2025

• Conducted high-frequency quantitative risk assessment and capital allocation under tight real-time constraints.
• Evaluated real-time odds discrepancies and statistical anomalies across multi-variable data streams.
• Applied strict probabilistic controls to limit drawdown and preserve capital efficiency.

Quality & Systems Engineer (M.Eng.) | Early Career

• Conducted audits, process validations, and safety compliance checks in line with strict industrial quality frameworks.
• Identified critical operational bottlenecks and implemented standardised data-logging procedures.
EDUCATION
Master of Engineering (M.Eng.)
Specialisation: Systems Quality & Safety Engineering