I am an "impact driven" data professional focused on solving real world problems leveraging art and science of data.
The approach I take towards problem solving is driven by the belief that models and frameworks are only valuable if they are adding value to solving a genuine issue. As such, when tackling any such task, I prioritize identifying the core (business) need before delving into the model building aspect.
Additionally, I hold the perspective that cutting-edge algorithms are not always essential for resolving problems. Sure, there are certain areas such as image recognition and NLP where conventional methods may fall short. However, based on my experience across various projects, I've found that a majority of use cases can be handled more effectively with traditional methods and algorithms (linear/tree based), as long as sufficient effort is invested in the process of domain-specific feature engineering.
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✨ I possess a comprehensive understanding of various data domains, including data engineering, business intelligence, business analytics, data science, and machine learning. Additionally, I have experience in managing DevOps and MLOps for machine learning projects.
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✨ I have a Masters in Business Analytics from National University of Singapore and have been working in the Financial Services industries (banking and insurance) for more than a decade.
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✨ My personal goals include developing solutions and frameworks that solve a real world problem or improves decision making in our daily lives.
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✨ In my spare time, I read and volunteer for General Assembly focusing on educating and empowering individuals with data skills.
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✨ I try to learn something new about Data Analytics and Machine Learning everyday. Check out what I am reading and evaluating here.
