Data Scientist
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Languages: Python, R, JavaScript, jQuery, HTML5, CSS3 Database Systems: MySQL, PostgreSQL, NoSQL (MongoDB) Cloud Services, DevOps & Big Data: AWS (S3, EC2, RDS), Docker, Git, Github, GCP, Azure, Hadoop, Spark Frameworks & Tools: PyTorch, TensorFlow, Angular, Flask, Figma, Django, Tableau, Power BI, Excel, Node.js Libraries: React, Keras, pandas, OpenCV, spaCy, Matplotlib, Scikit-learn, NLTK, Hugging Face, Plotly, NumPy, SciPy AI: Machine Learning, Deep Learning, Neural Network, Computer Vision, NLP, Reinforcement Learning Algorithms: KNN, Random Forest, Decision Tree, Regression, Clustering, Classification, Bagging, Boosting, PCA, GAN AI/Data Science Skills: Data collection, preprocessing, model training, evaluation, visualization, statistical analysis Digital Marketing: Google Tag Manager, Google Analytics, Adobe Analytics, Google Search Console, Ahrefs, Moz