Client Support & Backend Workflows Automation

• Built and maintained backend modules for a rendering SaaS using Python.

• Developed a chatbot to automate communication between technical support and clients.

• Managed and optimised MariaDB and PostgreSQL databases for internal tools.

• Collected and preprocessed data to build a time prediction model that improved the accuracy of rendering job estimates.

• Designed and implemented a visual predictive model using synthetic data for internal research.

• Built a sentiment analysis tool to assess user feedback and created a recommendation system based on user behaviour patterns.

Led a team of 3 developers in designing and maintaining RuBackup’s software ecosystem.

Designed and implemented a modular Python library for backup integrations, now published on PyPi.

Released the first stable version of the web interface and REST API for RuBackup’s backup control system.

Developed and deployed an autoregressive model using statsmodels to predict remaining storage capacity.

Formalised internal coding standards, GitLab practices, and documentation processes to improve code quality and maintainability.

• Trained a computer vision model to detect vehicle scratches and damage from images.

• Built a containerised service using Docker for model deployment.

• Enhanced image preprocessing pipeline to boost model accuracy and generalisation.

Managing cross-functional teams and facilitating collaboration across diverse program positions. I act as a bridge between technical AI teams and various business units ensuring seamless integration and deployment of AI solutions. I manage third-party applications to make sure AI tools work smoothly, using tools like EazyBI to make key metrics, Google Sheets Excel and specific charts for Agile teams.