Ngassa Courad Kwetchua

I am a data analyst, machine learning , data scientist, NLP etc practitioner. I have a bachelor degree in Applied Physics & Computer science and now concluding my master of science in Data Engineering & Analytics at the Technical University of Munich, Germany.

Review pricing structure and recommend changes based on analysis of performance of different customer segments
Review external data sources for value to insurance pricing and make recommendations
Create and run regular reports that highlights performance by different segments
Machine Learning(Insurance Pricing & Analytic) Predictive Analytic for Pricing optimization

Review pricing structure and recommend changes based on analysis of performance of different customer segments
Review external data sources for value to insurance pricing and make recommendations
Create and run regular reports that highlights performance by different segments
Machine Learning(Insurance Pricing & Analytic) Predictive Analytic for Pricing optimization

Identification of themes arising from reflections on speculative design artifacts using Natural Learning Processing
Data Analyst at European i-DREAMS Project, TUM Germany
Data Collection and analyzing driver behavior from naturalistic data for data-driven and managerial decisions
Machine Learning for predicting dangerous driving zones for safety purpose
Model creation for predicting the duration of these dangerous zones

Identifying the patterns of advertisement data and following the data trends on customer’s bundles purchases for new products on monthly bases
Worked with structured and unstructured dataset collected from the organization’s database using SQL and analyzing it statistically for managerial decisions on customer satisfaction
Developed a trend forecasting model to identify MTN products selection alternatives for customers usage

OData service, Data collection from SAP UCC Munich database and send the data to the frontend
Creating entity link to transport collected data to the frontend
Creation of CRUD methods and functions for building a monitoring application in SAP

Extracting future mobility technologies related data on social media (Twitter)
Mining social media data (Twitter)
Analyzing what the public is thinking on future mobility technologies using sentiment analysis
Classification of public opinions as positive and negative and deriving the central topics and arguments from twitter posts
Using and combine existing data mining techniques to derive insights on the topic of future mobility technologies

Using SQL to query the organization’s database for the analysis of network subscribers on monthly bases
Using Statistical techniques and mathematical tools to visualize and achieve better insight of the customer’s data
Creation of CRUD methods and functions for building a monitoring application in SAP

Defined and tracked the various KPI’s of Orange customers using machine learning algorithms for strategic decisions based on customer subscribers data on quarterly bases
Using SQL to query data and improved data accuracy and viability by streamlining processes regarding data flow and data quality
Supported management’s heads to identify opportunities for operational improvement and strategic decisions based on the organization data

Data Collection and analyzing driver behavior from naturalistic data for data-driven and managerial decisions
Machine Learning for predicting dangerous driving zones for safety purpose
Model creation for predicting the duration of these dangerous zones