Elena

ELENA GRYGORIEVA​
Junior Python Developer | Backend & Data Enthusiast​
Norway (Open to Remote)

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GitHub: https://github.com/NOva-El​
LinkedIn: [открыть контакты](см. выше в блоке «контактная информация»)

PROFESSIONAL SUMMARY

Junior Backend Developer with hands-on experience building Python-based applications,
API integrations, and data-driven projects.

Experienced in designing backend logic, integrating external APIs (Telegram, Google
Calendar), working with SQL databases, and applying data analysis techniques using
Pandas and scikit-learn.

Strong focus on clean, structured code, automation, and practical problem-solving. Seeking
a backend-focused role where I can contribute to real systems while continuing to grow in
data and system design.

TECHNICAL SKILLS

Programming

●​ Python (OOP, functions, modular design, error handling)​

●​ SQL (SELECT, JOIN, filtering, basic schema design)​

Backend & APIs

●​ REST principles​

●​ Telegram Bot API integration​

●​ Google Calendar API integration​

●​ JSON handling​

●​ Input validation & business logic implementation​

●​ Basic knowledge of Django / Flask concepts​
Data & Machine Learning

●​ Pandas (data cleaning, transformation)​

●​ NumPy (array operations)​

●​ Matplotlib (data visualization)​

●​ scikit-learn (model training & evaluation)​

●​ Exploratory Data Analysis (EDA)​

Tools

●​ Git (branching, pull requests, version control workflow)​

●​ GitHub (documentation, repositories)​

●​ PyCharm​

●​ Jupyter Notebook​

●​ Command Line

PROJECT EXPERIENCE

Telegram Booking Bot (Python)

●​ Developed a Telegram bot for appointment scheduling
●​ Integrated Google Calendar API for real-time booking synchronization
●​ Implemented booking logic, validation, and user interaction flow
●​ Structured backend logic for automation and scheduling

Smart Pricing Engine (Python)

●​ Designed rules-based pricing system with discounts, delivery, and tax logic
●​ Built modular and maintainable backend structure
●​ Implemented business logic simulation and validation

Customer Churn Prediction (Machine Learning Project)

●​ Conducted exploratory data analysis (EDA)
●​ Cleaned and processed data using Pandas
●​ Built and evaluated ML models using scikit-learn
●​ Extracted business-oriented insights from model results

Percentage Calculator (Python)
 ●​ Built from scratch using structured Python logic
●​ Implemented input validation and real-world financial calculations

Full portfolio:​
https://github.com/NOva-El

EDUCATION

Makeevka Institute of Economics and Humanities​
Bachelor’s Degree, Law

DataCamp – Data Science Track​
Completed structured training in Python, data analysis, and practical coding exercises.

Kaggle – Python Practice & Problem-Solving​
Hands-on coding exercises and applied problem-solving using real datasets.

KEY STRENGTHS

●​ Strong learning mindset and fast adaptation​

●​ Structured and logical problem-solving approach​

●​ Comfortable reading documentation and applying new concepts​

●​ Attention to code clarity and organization​

●​ User-oriented thinking