Data Scientist at Etisalat

I always loved the idea human-like models that run autonomously with minimal human supervision as well as my passion in visualizing and analyzing data to tell a story and draw actionable decisions and that's when it all begun when I started learning data science and machine learning by joining the 9 month ITI data science diploma. Since then I started my career as a data scientist.

The most interesting thing about my work is applying machine learning algorithms to different datasets to help the business make better decisions and make some teams work easier and better. Maybe the most thing I like in this field is the chance to do both, the technical IT work as well as being involved in the business cycle and decision making process.

Beside machine learning, one of my key strengths appears when it comes to creating dashboards using visualization tools like Tableau and creating business presentations.


The role as a data scientist is:
o Working with McKinsey team on creating and supporting different ongoing machine learning models and creating A/B test groups for testing.
o Developed “Recharge Prediction Model” using XGBoost algorithm that predict customers who will recharge in the next 2 days.
o Developed “Customer Complaint Prediction Model” using Gradient Boosting algorithm that predict customers who will contact the call center daily to complain and the reason for the complain to be able to handle them proactively
o Assisted in developing “Dual-Sim Carriers Prediction” model using Random Forest algorithm that predict customers who carry dual sim cards.
o Developed clustering model using GMM to divide Etisalat Stores into groups used in setting stretch targets and identifying each store real selling potential.
o Developed a risk scoring model to estimate the risk for each customer to determine customer eligibility on installment plans.
o Worked with different departments on different analytical reports.

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