About Me.
Hi there!
I’m a passionate and curious individual who loves exploring the world of Machine Learning and Data Science. What excites me the most about these fields is their potential to solve real-world problems and uncover patterns that inspire innovative solutions.
Currently, I’m pursuing my Master’s at Arizona State University, where I’m diving deeper into understanding how data shapes our world. I enjoy finding insights, tackling challenges, and crafting solutions that make an impact.
Beyond work, I’m a lifelong learner who enjoys taking on new challenges, whether brainstorming ideas, exploring creative hobbies like videography, or collaborating with people from diverse backgrounds.
Feel free to explore my site, check out my projects, and connect with me. I’d love to hear your story too!
Education
August 2024 - May 2026
Arizona State University
Masters in Data Science, Analytics, and Engineering
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Focus Areas: Machine Learning, Data Analysis, Predictive Modeling, and Big Data Engineering
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Highlights: Advanced coursework in statistical modeling, LLM fine-tuning, and real-world data applications
August 2020 - June 2024
MIT- WPU
Bachelor of Technology in Electronics and Communication Engineering
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GPA: 9.59/10 (3.84/4)
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Key Achievements: Good understanding and top grades in mathematics, calculus-related subjects and programming. Developed a hybrid IoT and data science animal tracking system for my Capstone.
Work Experience
August 2023 - January 2024
May 2022 - June 2023
Data Engineer Internship
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Centre for Technology, Innovation and Economic Research (CTIER)
Engineered a robust tool for transforming and analyzing unstructured data, enabling predictive insights and supporting strategic decision-making. Designed and implemented automated ETL workflows and data pipelines for seamless data integration and real-time analytics, complemented by dynamic data visualizations to communicate key insights effectively. Leveraged skills in Python, SQL, NLP, LLMs, Hadoop, R, Azure Data Factory, ETL workflows, SAS, JSON/NoSQL databases, regression and probability analysis, data pipelines, and JavaScript to deliver impactful solutions.
Data Analytics Internship
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Tripolarcon
Improved operational efficiency by developing predictive models and streamlining inventory management processes, achieving a 15% reduction in delay errors. Designed and implemented dynamic dashboards using Power BI and Tableau to visualize key performance indicators and enable real-time, data-driven decision-making. Utilized expertise in Python, SQL/NoSQL databases, SQL Server, Oracle, Snowflake, AWS, Azure Data Factory, ETL processes, React, Node.js, data wrangling, and predictive modeling to deliver impactful solutions for warehouse operations.
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