1+ years of experience in data science and deep learning with strong computer vision and algorithmic problem-solving ability. ‎Wide range of experience in data science/ machine learning/ deep learning space from simple machine learning algorithms to complex deep learning neural networks. Working Technologies: - Python, Julia, C++, MATLAB; - Practical Statistics for Data Scientists: Exploratory data analysis, Data distribution, Statistical experiment, Significance testing; - Computer Vision dataset collection and preparation, Training Pipeline, CNN Model Deployment; - Data preprocessing: Data quality assessment, Feature aggregation, Feature sampling, Dimensionality reduction, Feature encoding; - Keras & TensorFlow, PyTorch, JAX, - NumPy, Pandas, Matplotlib, Scikit-learn, Seaborn, OpenCV, WandB; - Real-time object detection and classification: SSD, EfficientDet, YOLOv5, etc.;