Data Science Engineer

The best time to plant a tree was 20 years ago the second best time is now. - Chinese proverb

🧾 Profile Summary

Experienced Data Science Engineer with a background in chemical engineering, passionate about building data pipelines, real-time dashboards, and machine learning solutions. Strong track record of deploying scalable analytics tools, mentoring teams, and delivering actionable insights from complex datasets.

⚡ Expertise: Python, SQL, Power BI, Streamlit, PySpark, Git, Redis
📍 Interests: Data Engineering, Operational Efficiency, Predictive Maintenance

💼 Working Experience

Data Science Engineer @ Coherent Corp

📅 September 2024 – Present

Developed enterprise-wide Power BI dashboards to monitor OEE (Overall Equipment Effectiveness), reducing manual reporting time by 60%.
Designed scalable ETL pipelines using Python, SQL, and PySpark, cutting data processing time by 50%.
Optimized SQL Server queries, slashing execution time by 97% and improving real-time monitoring.
Built production-grade Git environments for collaborative analytics workflows.
Mentored 2 batches of interns on Streamlit apps, automating performance monitoring tools.

Reliability Engineer @ Jacobs Douwe Egberts

📅 October 2022 – September 2024

Created real-time KPI dashboards with Power BI for machine reliability tracking.
Analyzed 25,000+ rows of raw data in one day to generate actionable insights for suppliers.
Led 5+ global coaching sessions on Microsoft 365 AI tools.
Designed master data structures for predictive maintenance strategies.
Reduced dehumidifier leakage by 80% with custom monitoring systems.

🎓 Education

MSc in Data Science (ODL) | Universiti Teknologi PETRONAS
📅 May 2024 – Sep 2025
CGPA: 3.91 / 4.00
Thesis: Development of Machine Learning Models for Failure Prediction in Oil & Gas Rotating Equipment
- One of the Postgraduate Awards receipients in MSc Data Science
BEng in Chemical Engineering (Hons) | Universiti Sains Malaysia
📅 Sep 2018 – Aug 2022
CGPA: 3.90 / 4.00
- Book Prize Recipient – School of Chemical Engineering
- Top 10 Final Year Project & Best Plant Design Team

📍 Featured Projects

🧠 Predictive Maintenance with Machine Learning

⚙️ Developed multi-sensor ML models to predict failures in refinery rotating equipment (pumps, compressors, turbines) using vibration, current, and temperature data.

📈 Achieved 99.9% accuracy with Random Forest, surpassing literature benchmarks, and demonstrated robust feature engineering and preprocessing workflows (MATLAB + Python).

📜 Presentation slides

📍 Garmin Analytic & Performance Dashboard

⏱️ An interactive web dashboard analyzing health & performance metrics from Garmin and Strava .csv / .fit exports.
🛠️ Built with Streamlit to visualize pace, heart rate, cadence, and GPS tracks.

⚡ A lightweight backend using Flask + Redis for managing user profiles, posts, and timelines.
Designed for real-time interactions using Redis data structures (hashes, lists, sets).

📦 CS50 Projects

🛠️ Predictive Maintenance (ML)

Used open-source predictive maintenance dataset.
Performed EDA, data cleaning, and trained a DecisionTreeClassifier — achieving 99.6% accuracy and 99.7% F1 score.

☀️ solaR R Package

Simplifies solar energy production data cleaning using R.

🧾 Maintenance Database (SQL)

Designed to support predictive maintenance:

Monitors equipment health
Predicts failure risks
Manages spare parts inventory

🧠 Skills & Tools

Languages: Python, SQL, R, DAX, PHP, MATLAB, VBA
Tools & Platforms: Power BI, Tableau, Power Automate, Git, GitHub Copilot, MongoDB, Redis, Docker, Azure, PySpark, SQL Server
Certifications:

CS50 Python, R & SQL – Harvard University
MATLAB Machine Learning Onramp
Snowflake ETL Mastery

🏅 Awards & Recognition

🎖️ 5th Place – SEA-GIC 2020 (58 teams, Southeast Asia)
📚 Book Prize – School of Chemical Engineering (USM)
🏆 Best Final Year Plant Design Team (USM)

🎤 Presentations

IChemE Workshop – Exploring Data Analytic Through Excel
📍 University of Nottingham Malaysia, March 2024