Нікіта

NIKITA
PEREHNIAK
DATA ANALYST | DATA
SCIENTIST

CONTACT ABOUT ME
Data Analyst skilled in Python, SQL, and ML. Recently
Valencia, Spain
achieved 101% of performance targets through data
[відкрити контакти](див. вище в блоці «контактна інформація») optimization. Proficient in ETL pipelines and Tableau
[відкрити контакти](див. вище в блоці «контактна інформація») visualization to transform raw data into actionable
business insights. Immediately available.
Kyivnik/github
Kyivnik/linkedin WORK EXPERIENCE
DATA ANALYST
EDUCATION
Hay Credito, Spain Jul2025 - Dec2025
BACHELOR - SYSTEM ANALYSIS Achieved 101% of monthly issuance targets and
Kyiv National Economic University optimized marketing acquisition costs by
2021-2025 performing deep-dive analysis of partner traffic
quality using Python (Pandas) and SQL.
ERASMUS - MATH & C.S.
Designed and implemented complex SQL-based
VSE Prague
conversion funnels to track the user journey from
2022-2023
registration to loan issuance, identifying key drop-
off points that led to a 15% improvement in
SKILL conversion.
Machine Learning & AI: Proactively identified and fixed critical database
Scikit‑learn, TensorFlow, logging errors by collaborating with the
PyTorch, XGBoost, engineering team, ensuring 100% data integrity for
hyperparameter tuning financial reporting and risk analysis.
Data Engineering: Python ETL,
Apache Airflow, BigQuery, SQL, DATA SCIENCE INTERN
data warehousing
UnIP Ukraine Jan2025 - Jun2025
Backend Development:
FastAPI, RESTful APIs, Docker, Developed a custom LSTM (Long Short-Term
GitHub Actions Memory) neural network for demand forecasting
Cloud Platforms: AWS (S3, using TensorFlow and Keras, achieving a 12%
Lambda, EC2), GCP (BigQuery, increase in accuracy compared to baseline models.
Cloud Functions) Engineered robust ETL pipelines using Python
Data Analysis & Visualization: (Pandas, NumPy) and SQL to clean, transform, and
Pandas, NumPy, Matplotlib, aggregate over 500,000+ records/week, creating a
Tableau, Google Data Studio unified dataset for machine learning tasks.
Tools & Methodologies: Conducted extensive Exploratory Data Analysis
Jupyter, Git, Jira, ClickUp
(EDA) and feature engineering to identify key sales
drivers, significantly improving model performance
and robustness.