I am a data scientist/Computer Vision engineer with more than 3.5 years of experience in Academia and 3 years of industrial experience in Computer vision, Machine Learning and Natural Language Processing, Python and c++ as well as packages TensorFlow, OpenCV, Keras, Scikit-learn. 
During my career, I have worked with both traditional machine learning, which incorporates features extraction, and modern end-to-end deep learning approaches. This career path has helped me to obtain in-depth knowledge of statistics, mathematics, and analytical skills in explaining the behavior of the algorithms based on the input data distribution and the algorithm output. My diverse career path, working as a machine learning researcher in academia and as a data scientist in a startup, consultancy company, and in a large corporation, has taught me to understand the heterogeneity of the business processes, working methodologies, and project needs of each scale.
My background in Machine Learning, Computer Vision, Natural Language Processing (NLP), Software Engineering and Algorithm has helped me to work in several parts of machine learning and I have performed the following tasks:

• Improve the accuracy of the existing machine learning models.
• Optimize the runtime and memory usage of the algorithms, since I have exceptional knowledge of algorithms, compilers, discrete math, and data structures.
• Analysis of experiments to improve clients' and business' needs.
• Select a suitable algorithm and its architecture to build new machine learning models.
• Evaluate and compare the results of different machine learning algorithms — model selection.
• Create clean and high-quality datasets.
• Build algorithms for critical systems.
• Integrate machine learning models in production.
• Innovat