Position: Machine Learning Engineer
Category: Data Science
English level: upper
Years of experience: 4

- Deep Learning and Machine Learning: Experienced in various data science methodologies, showcasing a understanding of deep learning and classical machine learning algorithms.

 - Statistical Analysis and Model Interpretation: Well-versed in advanced exploratory data analysis techniques and model explanation tools.

 - Client Collaboration: Effective in fostering strong relationships with clients through daily communication, focusing on establishing goals, monitoring progress, and ensuring successful project outcomes.

 - ML Guidance, Idea Generation and Integration: Proficient in guiding team to develop and implement machine learning solutions, while generating innovative ideas and effectively incorporating them into projects, contributing to continuous improvement and delivering value-added solutions for clients.
I have worked with projects in various fields:

 - Computer Vision: 3D point cloud scene segmentation/part segmentation/object detection, 2D segmentation/object detection/classification, diagrams parsing (created big pipeline for this project: 4 different datasets with 4 different ML models);

 - Classical Data Science: predicting prices for car insurance; predicting whether delivery will be completed; multioutput regression (time estimation for roles in project);

 - Private ML: usage of differential privacy mechanisms;

 - NLP: text summarization, generation, classification (also using transformers), parsing pptx/pdf file formats with division into blocks/chapters;

 - Survival analysis
I want to work in the field of Data Science/Machine Learning/Computer vision and further improve myself in this; find good team to work with; gain interesting experience on hard projects.