Data Science Graduate | AI/ML Enthusiast | Technical Problem Solver
I'm currently pursuing a Master’s in Data Science (AI/ML specialization) at Deakin University, with hands-on focus on applied machine learning, deep learning, generative AI, and cloud-based solutions. My journey centers on using cutting-edge tools and algorithms to unlock insights, automate processes, and drive innovation—across domains.
I enjoy experimenting, open-source collaboration, and sharing insights with the global data community. My professional philosophy is to build solutions that are practical, scalable, and empower confident decision-making.
Alongside my studies, I work as an Associate Consultant in Product Analytics at Eli Lilly, with 4 years+ experience in delivering data-driven solutions and analytical products that enhance efficiency, standardize processes, and drive impactful business outcomes.
- Languages & Libraries: Python, Pandas, Scipy, Scikit-Learn
- Machine Learning & AI Frameworks: TensorFlow, Keras, Deep Learning, Artificial Intelligence, Machine Learning
- Natural Language Processing/Generative AI: Hugging Face, Transformer, LangChain
- Data Engineering & Cloud: SQL & Databricks
- Visualization/UI: Gradio, Tableau, Power BI, OpenCV
- Additional Tools: Jira, GitHub, Microsoft Office Suite
- Built real-world data science and machine learning projects using 20+ tools and libraries
- Hands-on with transformer models, generative AI, NLP, and prompt engineering
- Prototyped end-to-end ML pipelines in Python, SQL, and cloud environments
- Gained exposure to big data processing and scalable analytics
- Collaborated in global, cross-disciplinary teams
- Building innovative ML/AI tools and demos with state-of-the-art frameworks
- Hands-on projects in generative AI, computer vision, NLP, and cloud analytics
- Exploring open source solutions and contributing to the data science community
- Seeking opportunities to apply advanced analytics and AI in diverse industries