Resume / Experience

EducatioN & Experience

Python Programming & Data Analysis, Applied Statistical Analysis with R
Data Management (SQL), Spreadsheet Modelling
Visual Analytics, Text Analytics, Social Analytics, Customer Analytics, Applied Machine Learning
Data Science for Business, Cybersecurity Technologies, Experimental Learning and Design, Financial Market Systems

Collaborate with internal customers using the GBI platform and help them to acquire and analyse data, create reports or dashboards for their business needs using MicroStrategy, Tableau, PowerBI and SQL
Automate existing work processes using machine learning to increase efficiency of work
Identify and troubleshoot production issues, and take responsibility for ongoing incidents, owning problems through to implementation
Integrating user feedback and business need, collaborate with product team to propose product enhancement requests and assist in implementation (e.g., design, testing)
Assist with updating training materials and participating in online and face-to-face training of users of the GBI platform

Extract, prepare and analyse customer insights and behaviour trends totalling up to 300+ cases on a daily basis
Employ PowerBI, Tableau and SAS Visual Analytics to generate operations dashboards, management reports and highlight actionable insights to senior management on streamlining operations for MOE’s annual exercises (e.g. Primary 1 registration, Secondary 1 posting).
Employed NLP models such as LDA for topic modelling and NLTK VADER for sentiment analysis to generate insights on customer behaviour and optimise customer handling SOP
Develop Python algorithms to improve efficiency of current data collection and report generation processes by 30%.
Forecast customer volume by analysing historical data and employing supervised machine learning algorithms such as time-series forecasting to optimise resource planning for the customer service team.
Utilise unsupervised machine learning algorithms such as clustering to detect emerging trends on customer issues and highlight to senior management for further action.

Designed a Python algorithm using NLP models such as LDA for topic modelling and clustering of public enquiries, highlighted key insights and solutions derived from results to improve on customer service metrics.
Utilised R for data cleaning and presented monthly reports based on existing and emergent customer issues.
Developed algorithms using machine learning and NLP to automatically categorise daily feedback and prioritise order of importance to improve efficiency of the customer service operations team.

Monitored and troubleshoot process operations proactively on a day-to-day basis by analysing real-time data and trends provided by fixed instruments and meters across the plant.
Reduced offspec product generated in 1 year by 100T(~$50k) by analysing data over 6-month period on ideal Operating Parameters and published SOPs based on trend analysis, reaction chemistry, reaction kinetics and safety.
Reduced offspec product generated in 1 year by 100T(~$50k) by analysing data over 6-month period on ideal Operating Parameters and published SOPs based on trend analysis, reaction chemistry, reaction kinetics and safety.

Bachelor’s Degree in Chemical Engineering (2nd Upper Honours)