Architecting Intelligent Systems with Data, from Concept to Deployment.

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My mission is to translate raw, complex data into intelligent, actionable solutions that drive growth and solve real-world problems. I build, not just analyze.

As a final-year Data Science honours student with a 3.95 GPA, my academic foundation is solid, but my true passion lies in the practical application of technology. I thrive on the entire project lifecycle: from defining a problem and engineering a robust data pipeline, to developing predictive models and deploying cutting-edge Generative AI systems. I believe in end-to-end ownership and pragmatic innovation.

• Data as a Language: I treat data not just as numbers, but as a language that tells a story. My goal is to become fluent in that language to uncover narratives that others might miss.
• Models as Tools, Not Oracles: I build machine learning models as powerful tools to solve specific problems, rigorously testing and evaluating them to understand their strengths and limitations.
• Pragmatic Innovation: I am deeply fascinated by the frontier of AI, especially LLMs. I focus on applying these powerful technologies to create tangible business value, not just for the sake of novelty.

Here are a few projects where I transformed an idea into a functional data-driven solution.

Keywords: Generative AI, LLM Integration, Machine Learning, E-commerce Trust & Safety

This system addresses a critical e-commerce challenge: identifying fraudulent product listings and communicating the risk effectively. It's a hybrid AI solution that combines the predictive power of classical ML with the summarization capabilities of modern LLMs.

• Impact: Creates a scalable system to enhance platform trust by automating fraud detection and accelerating human-in-the-loop review processes with AI-generated summaries.
• Tech Stack: Python, Pandas, Scikit-Learn, Large Language Models (IBM Granite).

Explore the Repository on GitHub

Keywords: Deep Learning, NLP, Customer Experience, TensorFlow

An end-to-end implementation to automatically analyze and classify customer sentiment from thousands of unstructured tweets. This tool is essential for any business aiming to understand its customer voice at scale.

• Impact: Delivers actionable insights from customer feedback in near real-time by automatically flagging negative comments, enabling customer service teams to prioritize intervention and improve service quality.
• Tech Stack: Python, TensorFlow, Keras (LSTM), Pandas, Scikit-Learn, NLTK.

Explore the Repository on GitHub

Keywords: Data Analysis, Market Research, Business Intelligence, Data Storytelling

A deep dive into a dataset of over 500,000 Google Play Store apps to provide a strategic blueprint for market entry and growth. This project moves beyond simple metrics to uncover the drivers of success in a saturated market.

• Impact: Empowers product managers and marketing teams with data-driven insights on pricing strategies, category competition, and features that correlate with user engagement and success.
• Tech Stack: Python, Pandas, NumPy, Matplotlib, Seaborn.

Explore the Repository on GitHub

My learning journey is ongoing. This is validated by 40+ certifications from industry leaders, focusing on the most relevant and emerging technologies in the data ecosystem.

Key Certifications:

• Cloud Practitioner Essentials (AWS Cloud) - Dicoding Indonesia
• Large Language Models (LLMs) Concepts & Generative AI for Business - DataCamp
• Data Engineering & ETL Subsystem - Altair RapidMiner & DQLab
• Deep Learning with Python Keras - BISA AI Academy

I am actively seeking challenging remote internship or part-time opportunities where I can contribute to a forward-thinking team and help solve complex problems.

If you're building something amazing, let's connect.

Say Hello → datasciencelatief@gmail.com```