Tulio Vargas's Linkedin Analytics

As a Data Scientist, my engineering background and MBA in Project Management and Business Technology empower me to harness data for impactful business results. Proficient in Python, Machine Learning, SQL, Azure, and AWS, along with data visualization tools, I've consistently delivered data-derived insights that steer strategic decision-making. I goals in problem-solving and finding creative solutions to complex problems. I also have strong communication skills, including the ability to present technical concepts in a clear and concise manner, and I'm experienced in collaborating with cross-functional teams. I'm always curious and willing to explore new technologies, programming laguagues and data sources to drive business value, and I have a strategic mindset to align data science projects with business objectives. My current focus involves crafting customer insights and fostering business prospects using Data Science, Statistics, and Business Intelligence. View my coding prowess and projects on GitHub: https://github.com/tuliovargasrj/datascience Python Programming – Strong proficiency in Python programming language. Writing modular and efficient code. Understanding data structures and algorithms. Machine Learning – Supervised learning (classification, regression), Unsupervised learning (clustering, dimensionality reduction), Neural networks and Deep Learning frameworks (TensorFlow, Keras, PyTorch), Natural Language Processing (NLTK, SpaCy), Computer Vision, Ensemble methods (Random Forests, Gradient Boosting). Data Analytics – Exploratory Data Analysis (EDA). Hypothesis testing and statistical analysis. A/B testing for experimentation Data Manipulation and Analysis – Pandas for data manipulation and preprocessing, NumPy, SciPy for scientific computing. Data Visualization – Matplotlib and Seaborn data visualization, Plotly for interactive visualizations. Database Skills – Advanced SQL for querying and data retrieval, (SQL Server, PostgreSQL, MySQL) NoSQL databases (MongoDB, Cassandra, Hadoop) Data Engineering – Data wrangling and cleaning techniques, ETL processes, data pipeline development. Working with big data frameworks like Apache Spark. Cloud Computing – Azure, AWS, or Google Cloud. Experience with cloud-based services. Web Development – With expertise in HTML, JavaScript, and CSS to build interactive and responsive user interfaces. Version Control – Git for version control and collaboration with teams. Scrum and Kanban – Practical experience working with Agile frameworks, including Scrum and Kanban, to efficiently manage and deliver projects.