Masters in Business Administration

Philippines

Grade: GWA 3.68Grade: GWA 3.68 / 4

Activities and societies:
-Feature Writer for The Magisine, the official publication of AGSB (2020-2021)

Notable Achievements:
- Silver Medalist
- Dean's Lister ( 2nd & 3rd Term, SY 2020-2021)
- My first technical paper has completed the peer review process and will be published in the 10th Volume of AGSB's Academic Journal: Techne.

Data Science Mentor

– Supervised and mentored students towards creating data science projects and presentations. Topic covered, Data Visualization, Web Scraping, Natural Language Processing, Supervised and Unsupervised Machine Learning and Network Analysis.

– Taught the basics and best practices of data analytics (data manipulation, data visualization, data storytelling and reporting) to a variety of learners , from college students to seasoned professionals.

– Mentored employees from corporate clients on how to code in python and how to use machine learning model in solving business problems.

Senior Data Scientist

Part of the R&D team that supports European financial institutions by creating the following solutions:

1. ML- and AI-Assisted Customer Profiling: Developed models to estimate Client Lifetime Value, Financial Literacy, and Communication Preferences using only existing banking data. For each dimension, designed and evaluated rule-based, machine learning, and LLM-driven approaches. Built a behavioral framework to infer financial literacy solely from customer transactions and interactions—no surveys or additional client input required.

AI Documentation Evaluation: Designed a quantitative evaluation system to measure the accuracy of AI-generated internal process documents by comparing them against manual (ground truth) versions.

Sales Analyst

The primary analyst responsible for competitor analytics , and supply chain management of the philippine sales department.

Selected projects include the following:

1. Automated Customer Sentiment Extraction – Developed an NLP model that analyzes and classifies email feedbacks by department (e.g., Customer Service, Products, Field Sales) and extract sentiment insights. The model enables swift action by routing feedback to the relevant teams, facilitating immediate resolution of issues such as app errors and aggressive sales tactics (individualized and data-driven coaching sessions are provided per sales agent based on customer feedback).

2. Time Series Forecasting with Machine Learning – Based on NeuralProphet, developed models that analyzes historical data to forecast key metrics such as sales volume, customer applications, and application traffic with minute-level precision. The model accounts for trends, seasonality, and time-specific events (e.g., local and international holidays) to deliver accurate and actionable predictions.

3. Subsidy report automation – the reporting process of computation of how much subsidy needs to be collected from partner brands on a monthly basis was automated in python. This lead to a faster collection process and reduction of the company’s financial float. overall processing time was reduced by 67%.

4. SalesCode Selection Streamlining Project – Led a cross-departmental project to automate the previously manual daily sales code selection process. each code enables specific promotions for individual stores. Mapped the existing process and implemented a Python-based solution to streamline it. Collaborated with the products team to standardize data formats and validate inputs, and worked with the operations team to ensure smooth integration into their daily tasks. This initiative lead to a reduction in processing errors and also a 91% reduction in processing time.

Customer Care Professional

– Account Handled: Credit Cards
– Provided world-class customer experience to clients in the U.S Market
– Was involved in an A/B testing program that created and compared multiple customer communication spiels to identify which one most reliably improves customer experience and business outcomes (As measured by survey responses and sales volume respectively)

Notable Achievements:
– in the top 10% for NPS for the scorecard year-end 2020

Subject Matter Expert

– Lead and trained batches of new hires to achieve multiple business targets on a monthly basis.
– Used excel pivot tables and charts to generate descriptive statistics that help identify the areas of improvement for each new hire.
– Reported the performance of each new hire batch to upper management for employment regularization discussions.

Six Sigma - Yellow Belt