Особисті дані приховані

CONTACT
Daniil Hutsol Phone: [відкрити контакти](див. вище в блоці «контактна інформація»)
Quantitative Methods in Economics student Email: [відкрити контакти](див. вище в блоці «контактна інформація»)

SUMMARY

Quantitative Methods in Economics student with strong analytical skills and attention to detail. Experienced in working
with structured data and building simulation-based models to support decision-making. Interested in financial markets
and passionate about working with data and numbers.

Relevant Experience Risk & Expected Value Simulation
& Projects Built Monte Carlo simulation to estimate pass probability, drawdown risk, and expected value
Modeled key parameters (win rate, risk-reward, risk per trade, loss limits)
Applied Random Forest to approximate outcomes and identify optimal strategies
Compared strategies under risk constraints to support decision-making

Bankruptcy Prediction System | Python, XGBoost, Optuna, SHAP Polish Companies Dataset (2000–2013)
Built an ML pipeline to predict corporate bankruptcy for bank credit risk screening:
Achieved ROC-AUC 0.86 and 90.9% recall on imbalanced dataset (~5% bankruptcy rate)
Reduced analyst workload by 57.5% by automatically clearing low-risk companies
Implemented MICE + RandomForest imputation for features with up to 39% missing values
Tuned XGBoost hyperparameters via Optuna (50 trials, F2-score objective) outperforming Random
Forest (Recall 90.9% vs 0.0%)
Applied SHAP analysis confirming economic consistency of model decisions (profitability, liquidity, debt
coverage)

EDUCATION

SGH Warsaw School of Economics
Bachelor in Quantitative Methods in Economics and Information Systems
Expected Graduation: 2027

Relevant coursework:
Statistics,Accounting, Econometrics, Macroeconomics

TECHNICAL
SKILLS
Microsoft Excel (Proficient: data analysis, spreadsheet-based simulations)
Power BI (Basic: data visualization, dashboards)
Python (Intermediate: data analysis, data processing)
R (Intermediate: statistical analysis)
SQL(basic)

CORE COMPETENCIES

Attention to detail
Data organization and structuring
Problem solving
Ability to work with deadlines

LANGUAGES
English (C1)
Polish (B1)
Russian (Native)
German (A1/A2 – Basic)
Ukrainian (Native)