Position: Data Scientist | Machine Learning Engineer
Category: Data Science
English level: upper
Years of experience: 5

- Strong math(Deep practical skills in the analysis of algorithms, good practical knowledge in next math disciplines with reference to computer science: discrete math, combinatorics, probability theory, statistics, asymptotic analysis. Great base math knowledge.)
- Deep understanding of fundamental DS/ML approaches
- Understanding of full-cycle DS/ML project serving
Throughout my career, I have gained extensive experience in the field of machine learning, with a focus on classical data science and computer vision. I have worked on a wide range of projects in computer vision, including object detection, segmentation, and pose estimation. My skill set includes classic image processing techniques and cutting-edge deep learning methods. In data science, I have a background in statistics, various machine learning techniques, advanced data exploration, model explanation tools, and deployment strategies.


Technologies which I use:

Engineering technologies stack: Docker, Flask, Flask-Socketio, multiprocessing + multithreading, edge devices integration(Jetson Nano), Windows integration(pyinstaller), PyQt, etc.

Data Science technologies stack: Pandas, Scikit-learn, XGBoost, LightGMB, Catboost, Facebook Prophet, model explanation tools(SHAP, SAGE, eli5, LIME), etc.

Computer vision technologies stack: image processing libraries(OpenCV, Scikit-Image, etc.), object detection and segmentation frameworks(YOLO, SSD, Faster R-CNN, Mask R-CNN, UNET), OCR(Tesseract), etc.

Deep learning technologies stack: Keras, PyTorch, TensorFlow, etc.
I am seeking an opportunity to join a team of experienced professionals where I can contribute my skills and experience while collaborating to make strategic decisions and develop impactful products.