WP. Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
Data Scientist skilled in Python, R, and machine learning models like XGBoost, Random Forest, and logistic regression. Quick to learn, solve complex problems efficiently, and apply solutions across various domains. Proficient in UiPath for RPA and SQL, with a proven track record of delivering cost-saving solutions. Experienced in presenting data-driven insights to top management, guiding decision-making, and driving measurable business outcomes.
Merchant Cash Advancement
1. Collaborated with MBSB Bank’s Liabilities & Proposition (L&P) team to develop three machine learning prediction models: • High Net Worth Identification, • Anti-Attrition, which flagged customers at risk of leaving—potentially retaining an estimated RM1 million, and • Early Redemption Prediction for fixed deposit breakages. 2. Developed ML models: a Propensity Model for unit trust and an MIA inflow (loan default) Prediction Model using Python & SQL, implementing the complete data science lifecycle, from data exploration and preprocessing to model development, evaluation, and deployment. 3. Fine-tuned the AML Threshold model using R to improve risk detection and compliance processes. 4. Developed a UiPath workflow that saved the bank MYR 14k and maintained older RPA workflows that helped sustain the bank’s efficiency. 5. Created RPA projects that automated critical functions for the bank—such as IIMM rate updates and COF-i rate updates—which helped avoid the need for additional hires and overtime pay. • These automations contributed to an estimated cost saving of RM3,000–RM5,000 per month, factoring in potential overtime and entry-level staff salaries in Malaysia. 6. Automated both critical & non-critical tasks to accelerate and streamline the bank’s data analysis processes coded in R, resulting in enhanced productivity. 7. Enhanced Power BI dashboards using SQL to ensure seamless data visualization and reporting, optimizing them for scalability and dynamic functionality. 8. Solved and developed ad hoc Power Query & SQL projects in a timely manner, enabling the company to address urgent data needs and enhance decision-making.
1. Led CDC project for Petronas PLI, developing optimized solutions in Talend and AWS GLUE using Python and SQL, addressing architectural ETL, ELT, and CDC challenges. 2. Optimized and restructured TM data flow and transformations using Talend, Impala, Hive, and Hadoop. 3. Developed a proof of concept for credit card fraud prediction using RapidMiner, incorporating insights from research on human patterns of digit usage, such as Benford's Law, and displayed results in Tableau. 4. Trained UNITEN lecturers on RapidMiner and Data Science. 5. Developed PowerBI reports using SQL.
1. Developed monthly SEO reports for companies like Toyota, Parkson, and Beauté Library. 2. In charge of searching and analyzing the best keywords and phrases for webpages for companies such as Toyota, Boost, Parkson, Beauté Library, and Levi's. 3. Enhanced coding and paragraphs of entire webpages to implement SEO.
1. Managed and executed installation and troubleshooting of hardware and software. 2. Taught employees to use newly installed software.