Chen Shen Email and Phone Number

Develop and implement data and analytic systems for over-the-counter fixed-income security trading. Responsibilities include system integration, financial report automation, developing trade recommender, and ALM sensitivity analysis under IFRS17.Key responsibilities include:► Integrated various financial reporting and trading systems to allow consistent and timely data consumption and reporting.► Leveraged big data to transform over-the-counter fixed-income trading practices by providing security-level and portfolio-level analytics.► Developed customized Python modules in Bloomberg to rank assets according to internal investment policies and automatically recommend to traders the best daily trades to execute.► Identified the optimal set of assets to buy/sell in order to provide the best asset-liability matching under the IFRS17 and the Canadian Asset Liability model guidelines.

At RBC Insurance, I lead the end-to-end development of best-in-class statistical models, resulting in a gain of over $15 million in profitability in 2019. To do so, I leveraged on a wealth of knowledge at RBC enterprise, and combining best practices in actuarial science, statistics, and machine learning.Furthermore, I founded the data community initiative to promote analytic strategies across RBC Insurance by organizing meetups to help stakeholders across various BUs identify opportunities to apply predictive analytics.Key responsibilities include:► Leading a team of data scientists and actuaries to consolidate external and internal insurance data,► Developing and implementing proprietary clustering algorithms to extract key information based on the policyholder's geospatial location.► Partnering with risk management and the pricing teams to replace traditional actuarial pricing framework with advanced statistical models for various insurance products on the market.

As a Contract Senior Data Consultant, I utilize predictive analytics to quantify values for residential homes and provide residual home-buyers and real estate agents with estimates of the house value within a particular postal code. The model was since used to select and purchase over $5 million dollars of residential properties.To do this, I apply R programming language to collect and scrape data from online housing ads in order to gather information on property sales price, postal code, the number of bedrooms, proximity to schools, etc. I then perform predictive analytics to determine proper housing prices.

As the sole Longevity Research Analyst, I work closely with senior business leaders across the company to implement the first longevity model that translates qualitative medical assumptions into a quantifiable impact on Canadian mortality.Additionally, I created deterministic models to quantify the impact of various "what-if" scenarios, such as breakthroughs in cancer treatments. I communicated my findings bi-monthly to senior business leaders and help to recommend actions in order to manage business risks.Significant Accomplishments include:► Received iSTAR Award for implementing a proprietary model that forecasts Canadian mortality rates based on quantifiable predictors such as exercise, smoking habits, and medical advances.► Lead the modeling process by independently creating and maintaining project plans, tracking deliverables of cross-functional teams including doctors, pharmacist and actuaries, and ensuring timely completion of critical milestones.► Cultivated buy-in from business leaders and well-respected experts in Sun Life including the chief medical doctor and the chief actuary in order gain alignment to get buy-ins.► Negotiated vendor contract to provide access to peer-reviewed papers at a lower cost resulting from $10k to 2k, a total of 8k in cost savings.

As a System Neuroscience Researcher within my MSc program, I published a well-cited research paper that classified regions of the brain responsible for detecting and compartmentalize learning errors in order to inform future decisions under the Reinforcement Learning framework (doi:10.1093/cercor/bhu028).I performed statistical analysis (PCA, Monte Carlos simulation) on big data, and collaborated with statisticians to implement a novel approach to classify regions of the brain that compartmentalizes error information.I communicated my research at international neuroscience conferences and my research paper has been cited more than 20 times within the first 2 years.

As a Teaching Assistant, I provided verbal explanation of key biological concepts and hands-on demonstration of proper experimental procedures to undergraduate students, and assessed their understanding by creating and grading quizzes and assignments.