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In the realm of data-driven problem-solving, I've found my calling—a passion for uncovering narratives and crafting solutions. As a data enthusiast, I thrive on analyzing complex information, making it actionable, and empowering informed decision-making.

With a solid foundation in data analytics and a double master's in data science and business analytics, I bring a robust skill set. Proficient in Python, SQL, R, C++, and C, I utilize tools like Jupyter Notebook, R Studio, Microsoft Excel, and data visualization platforms such as Plotly-Dash, Power BI, and Tableau.

My expertise extends to statistical analysis, machine learning, and deep learning, encompassing regression, classification, clustering, and NLP techniques. Familiar with databases like SQL Server, PostgreSQL, and MySQL, I bring a holistic approach to problem-solving.

Beyond technical skills, my strengths lie in collaboration, storytelling, adaptability, leadership, and effective problem-solving. These competencies ensure that my data-driven endeavors are not only technically sound but also collaborative and impactful, turning insights into compelling stories.

Programming Languages: Python, R, My-SQL (SSMS, Databricks, Redshift & Mongo DB), C++, C, Java

Analytics: Data Mining, Machine Learning, Data Visualization, Data Engineering, Predictive Analytics, Statistical Analysis (AB Testing)

Tools/Framework: Tableau, AWS, PowerBI (DAX), Jupyter Notebook, R Studio, Azure, Hadoop, Scala, Excel, Flask, Postman, API’s

Libraries – TensorFlow, NumPy, Pandas, Scikit-Learn, NLTK, Keras, Matplotlib, Seaborn, PyTest, PySpark, Amazon Athena, Dash, GAN