Ірина

IRYNA GITIS
Data Scientist / AI Researcher
Location: Ukraine | Email: [відкрити контакти](див. вище в блоці «контактна інформація») | LinkedIn: [відкрити контакти](див. вище в блоці «контактна інформація»)
GitHub: github.com/gitis-iryna | ORCID: orcid.org/0009-0009-9091-8854

PROFESSIONAL SUMMARY
Data Scientist and AI Researcher with a Master's degree in Computer Science (specializing in AI Systems). Deep technical
background in designing, training, and evaluating neural networks across diverse domains, including socio-economic
forecasting, NLP pipelines, and complex stochastic decision-support systems. Combines strong mathematical grounding
with expertise in predictive modeling, time-series analysis, and certified C1 English proficiency.

SKILLS
• Domains & Core: Machine Learning, Deep Learning, NLP, Reinforcement Learning, Time Series Analysis and
Forecasting, Predictive Modeling.
• Languages & Libraries: Python, SQL, Matplotlib, TensorFlow, scikit-learn, Pandas, NumPy.
• Architectures & Algorithms: RNN, LSTM, BiLSTM, GRU, Transformers (BART), CNN, FFNN, MCTS, PPO.
• Tools: Data Preprocessing, Exploratory Data Analysis (EDA), Feature Engineering, Git/GitHub, Google Colab.

RESEARCH & TECHNICAL EXPERIENCE
AI Researcher & Data Scientist (Academic R&D) | 2025 – 2026
• EDA & Feature Engineering: Conducted an in-depth analysis of tyre stochastic degradation data; developed
custom features to accurately represent wear in RL and MCTS models.
• Data Preprocessing: Implemented a time series pre-processing pipeline, using forward/backward filling to prevent
data leakage, and mapped continuous telemetry variables to discrete classification labels.
• Stochastic Decision-Support Systems: Engineered AI-driven decision models under conditions of stochastic
uncertainty (applied to F1 race strategy). Conducted comparative analysis of Monte Carlo Tree Search (MCTS) vs.
Reinforcement Learning agents across 100+ dynamic simulations.
• Complex Time-Series & Predictive Modeling: Researched RNN architectures for degradation forecasting,
incorporating mechanical and physical constraints.
• Cross-Domain Time-Series Forecasting: Applied Long Short-Term Memory (LSTM) networks to non-technical
domains, successfully developing robust predictive models for labor market dynamics.
• Natural Language Processing: Designed a Named Entity Recognition (NER) pipeline utilizing a BiLSTM architecture
and GloVe embeddings. Expanded NLP expertise by performing sentiment analysis and working with Large
Language Models (LLMs) and Generative AI (including BART architecture) for advanced text processing.
Higher Education Quality Assurance Expert | National Agency for Higher Education Quality Assurance | 2025 – Present
• Conducted thorough structural audits and academic quality assessments.
• Optimized data processes, prepared extensive technical and procedural documentation, and translated
institutional metrics into actionable recommendations for infrastructure improvements.

PUBLICATIONS & RESEARCH
• Motorsport Strategy & AI: Neural Network Decision Support System for Formulating a Racing Team Strategy |
10.31891/csit-2025-2-17. Detailed the architecture and implementation of AI-driven decision-support models for
dynamic race environments.
• Labor Market Predictive Modeling: Прогнозування динаміки попиту та пропозиції на ринку праці України |
10.31891/2307-5740-2025-340-10. Applied RNN to analyze and predict complex national socio-economic trends.
• Educational Data Analytics: Forecasting the Success of Education Seekers from a Separate Educational Component
Based on the Results of the Preliminary Mastery of Subject Competencies | 10.31891/csit-2024-2-6. Developed
predictive models to evaluate and forecast student performance utilizing historical academic competency data.

EDUCATION
Kharkiv National University of Radio Electronics | Kharkiv, Ukraine
Master of Science in Computer Science (Program: Artificial Intelligence Systems) – With Honors | Graduated 2026
• Thesis: Research on Artificial Intelligence Methods for Racing Strategy Formulation under Stochastic Uncertainty.
Bachelor of Science in Computer Science (Program: Artificial Intelligence) – With Honors | Graduated 2024

CERTIFICATIONS & LANGUAGES
• Languages: English (C1 Level) – B2 First (FCE) Certificate, Cambridge Assessment English.
• Certifications: Natural Language Processing Specializations (Coursera) | Wildau-Kharkiv IT Bridge II, DAAD
Programme: "Digital Ukraine" (2023).