Bell Jotio
Master's degree in financial engineering
Cohort 2023
HEC Montréal
Master's degree in financial engineering
Cohort 2023
HEC Montréal
Master's degree in financial engineering
HEC Montréal
Master's
I am a Computer Design Engineer graduated from the Ecole Nationale Supérieure Polytechnique of Yaoundé in Cameroon, and a student in Master of Financial Engineering at HEC Montreal, thesis option. My most recent diplomas are Scientific Baccalaureate with good mention and Engineering degree with excellent mention. My technical skills are: Data analysis, numerical computation, stochastic computation, risk management, portfolio management, asset pricing, statistics, mobile programmer, data visualization, data modeling and formalization, Mathematical model design, algorithm design, logic, recommendation system. My Cross-functional skills are: Scrum Master, ITIL, Marketing and Communication, Project Management, Fundamental Insurance, Tutoring, Driving etc. And my Working tools are: Ms Project, Word, Excel, Matlab, Bloomberg, Python, Flutter, Dart, Numpy, Scipy, Seaborn, Sklearn, Pickles, Hdfs, Apache Spark, Apache NIFI, Sql, Hive, Hadoop, Power BI, Grafana etc.
I am Jotio Bell, I am interested in artificial intelligence, finance, mobile programming, big data and mathematics. I particularly like the problems of creating optimal decision models and recommendation systems. I also like the design and mathematical modeling of problems to solve them with artificial intelligence algorithms. In particular classification problems, prediction models and optimization problems. I am a disciplined, open-minded, orderly, meticulous, rigorous and hard-working person.
Trakins: Building a real time smart insurance broker using NLP and Computer Vision
Trakins is an application that aims to help users better understand and manage their insurance portfolio. To do this, users must submit relevant information about themselves and their current contracts in forms provided in the Trakins application. Based on these information and information from the insurance market, THEGA is about to develop a decision-making model that can effectively answer questions about customers and their insurance portfolio. This includes, for example, saying whether the customer’s contract is optimal, offering new market opportunities to the customer in real time, saying whether the customer’s contract has duplicates, and helping the customer to check his insu- rance coverage.
As a part of the implementation of the TRAKINS solution, we proposed a decision model consisting of a hybrid recommendation system such as switching and increased functionality. This involves first designing a collaborative recommendation strategy based on KNN, K-means classification algorithms and a so-called pre-recommendation tactic and secondly building a contract optimization engine for content recommendation based on linear programming algorithms such as the simplex method and the so-called binary matrix algorithm. The recommendation was "notationless", which means that the system isn’t able to benefit from a product rating mechanism because the rating process was very long. Our challenge was also to overcome this handicap.
Currently looking for an internship
Prefered Starting Date: 01/05/2023
Prefered Theme: Modelisation, Datascience, Risk management
