Data and business analyst

Royal Bank of Canada

Developed the supervised and unsupervised anomaly detection model using Spark to identify any irregular records on the client’s risk rating data which help ensure the correctness of the capital calculation and BCAR report. || Assisted in the migration of the Capital Measurement Data (BCAR System) by gathering and analyzing the user’s BAU and requirement to identify if there is any gap between the old and new system that need to be addressed. || Led operations in finding the automated business process tool by gathering and developing the requirements and use-cases, and finding and selecting the vendors. || (Volunteer) Helped the RBC’s employee experience team in drawing insight from the employee experience survey using different natural language processing (NLP) methods such as topic modeling or sentiment analysis.

• May 2016 - August 2016

Data scientist (aml)

Royal Bank of Canada

Researched and developed a graph-based behavior anomaly detection model and community detection which utilizes both relation and transaction information within the transactional network using graph neural network. || Extracted the flow of indirect transaction of the target parties from the large internal database via SQL and python and making use of text similarity, fuzzy matching, and embedding techniques. || Developed name-entity (NLP) classification models that predict a person’s origin based on the person’s name using different models such as TF-IDF, fastText, and LSTM. || Utilizing the geo-location data and transaction information to identify the potential benefit fraud as part of the COVID-19 Hackathon’s RBC’s AML event.

• Jan 2020 - April 2020

Teaching assistant

University of Waterloo

Performed all assistant teaching duties, including mentoring, lecturing, and researching for both undergraduate and graduate courses, including Classification, Advanced Regression, Linear Model, and Computational statistics course. || Provided additional support by conducting virtual one-on-ones with the students during the pandemic lockdown.

• Link: https://github.com/thisisphume/TA_STAT_UWaterloo

• May 2016 - August 2016

People analytics and consultant

Aon

Developed interpretable machine learning to analyze different types of employee data such as engagement survey, compensation, personality-behavior assessment test, using Python, and R to provide insight and recommendation to the stakeholder. | Managed multiple projects as the project manager, developed trusted relationships with clients, and developed new business opportunities for Employee Engagement and People & Organization Transformation projects. | Developed multiple data-driven solutions such as Organizational Network Analysis, Text Analytics, Culture Fit Model, Employee Segmentation as part of Aon’s new data analytics team

• August 2018 - August 2019

Data scientist (innovation)

Royal Bank of Canada

Selected for intensive RBC Amplified summer program to solve a business challenge in an Agile environment and present solutions to senior leaders including the CTO || Winner of two Amplify awards, the Judges Choice Award ($15,000) and the Viewer’s Choice Award ($5000) || Leveraged data within RBC to create a survival model which predicted the probability of future incident within the RBC’s Personal and Commercial Retail Bank using Python || Built a mathematical model to calculate the business impact of each production incident || Assisted in developing an interactive dashboard and monitoring tool using Elasticsearch, Grafana for indexing and visualizing data, and Python for retrieving and pre-processing the data || Co-Inventor patent- System for Network Incident Management, publication number 20180054363

• May 2016 - August 2016