Загруженный файл CV

PERSONAL INFORMATION

Chisinau, Moldova
Date of birth: 27 June 2003
Nationality: Ukrainian

LANGUAGES

• Ukrainian - native
• English - B2
• Russian - fluent
• Romanian - A1

KEY SKILLS

• Python
• Azure ML
• PyTorch
• YOLOV5
• OpenCV
• NumPy
• Pandas
• SQL
• Power BI
• DAX
• Power Query M

Curriculum Vitae

Full-Time Data Analyst | Data Science & Power BI Focus

PROFILE

Software Engineer/Data Scientist with 2.5 years of hands-on experience in image recognition workflows, object detection model training, SQL-based analysis, Power BI reporting and Azure ML environments. Focused on improving ML processes, dataset quality and recognition results through data preparation, hyperparameter experiments, automation and clear analytical outputs. Combines technical background with creativity, responsibility and the ability to communicate clearly with both technical and non-technical colleagues.

Looking for a full-time Data Analyst position, preferably remote or hybrid, where I can clean and analyze data, build Power BI dashboards, prepare SQL-based reports, automate repetitive analytical tasks and apply data science experience to help teams make clearer data-driven decisions.

WORK EXPERIENCE

Data Scientist | IPLAND
09 Jan 2024 - Present | Kyiv, Ukraine - remote

"effie>" - is an Al platform for sales strategy management, trade marketing operations at points of sale and optimization of relationships between manufacturers, distributors and retailers.

Responsibilities

• Developed, trained and evaluated image recognition and object detection models in Azure ML and YOLOv5/PyTorch workflows.
• Analyzed model quality, dataset distribution, recognition errors and class/label mapping to identify practical improvements.
• Optimized recognition results using hyperparameter experiments, dataset corrections, artificial datasets and validation checks.
• Prepared and converted training data, annotations, MLTable/JSONL assets and mobile neural network datasets for repeatable experiments.
• Automated routine ML and data preparation steps with Python, SQL, Pandas/NumPy and OpenCV, reducing manual work and errors.
• Created Power BI and SQL-based analytical outputs for model performance, recognition quality and process monitoring.

Achievements

• Controlled and improved quality for 100+ recognition models used in real business workflows.
• Optimized the neural network training and testing workflow by reducing unnecessary steps and speeding up result delivery.
• Improved experiment repeatability by structuring dataset preparation, conversion and validation processes.
• Transferred the neural network training process to technical support colleagues, making the workflow more scalable and understandable.

DIGITAL SKILLS

• ML model training, evaluation and optimization for image recognition and object detection.
• Python for dataset preparation, annotation conversion, data processing and ML workflow automation.
• Experience with Azure ML, MLTable/JSONL datasets and deployment-oriented training workflows.
• SQL and Power BI for analytical outputs, quality checks, reporting and visual presentation of data.
• Advanced user of Microsoft Excel, Word, PowerPoint, Google Sheets and Google Docs.

HOBBIES

• Travelling and mountain hiking.
• Vocal practice and music.
• Go and Mahjong.
• Volunteering.
• Game design.
• Quizzes and intellectual games.
• Creating Excel spreadsheets for everything that can possibly be structured.

EDUCATION AND TRAINING

Bachelor in Software Engineering | Kyiv Aviation Institute
2021-2025 | Kyiv, Ukraine

Thesis: "A tool for analyzing the influence of hyperparameters and dataset distribution on the quality of an object recognition model in photographs."

SOFT SKILLS

• Responsible and reliable in routine and detail-oriented tasks.
• Creative in finding non-standard solutions to technical and analytical problems.
• Adaptive and quick to learn new tools, workflows and business contexts.
• Communicative and able to build common ground with colleagues and stakeholders.
• Organized and focused on clear, practical results.

Language levels:
Ukrainian (5/5)
English (3/5)
Russian (4/5)
Romanian (1/5)