🎓 Data Scientist with a background in computational physics, bringing a passion for solving complex business problems through data-driven insights. With experience spanning across data analytics, machine learning, and computational modeling, I have worked on projects in fields like healthcare, precision agriculture, climate change, and credit risk modeling.

With over a year of experience in data science and machine learning, I specialize in applying statistical analysis and advanced machine learning techniques to address real-world challenges. My prior research experience in computational physics adds a strong foundation in mathematical and computational modeling, enabling me to tackle problems in various domains.

In my research career, I authored seven publications on computational materials modeling, presented at international conferences, and contributed to the Deep Underground Neutrino Experiment (DUNE) at Fermilab, simulating neutrino-matter interactions.

• 📊 Data Analytics
• 🧠 Machine Learning and MLOps
• 🧪 Hypothesis Testing, A/B Testing, and Causal Inference
• 🔬 Mathematical and Computational Modeling
• 📈 Data Visualization
• 🎯 Project Management
• 🤝 Cross-Functional Collaboration

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  • Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, PyTorch, TensorFlow/Keras)

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  • SQL for data querying and management

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  • Power BI, Tableau, Microsoft Excel for advanced data visualization and insights

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  • AWS, Azure for cloud-based computing and model deployment

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  • Flask, FastAPI for building scalable web applications

• Working on Credit Risk Modeling and Marketing Analytics projects using data analysis and machine learning techniques.
• Exploring Deep Learning, Natural Language Processing, and Generative AI to expand my skill set.

• 📧 Reach me at: [email protected]
• 💼 Connect on LinkedIn

By combining strong technical expertise with a collaborative mindset, I aim to contribute to impactful data science projects that drive real-world solutions.