Amir Ragab

Senior Data Scientist at e&

About Me

I am a Senior Data Scientist at e& enterprise based in UAE, with an experience of over 5 years in Data, Analytics, and AI.

Technologies/ Tools

Python / R

Tensorflow

Machine learning / Deep Learning

Data Analysis

Tensorflow / Pytorch

PowerBI / Tableau

Microsoft Azure Fabric

DataBricks

NNs, CNNs, RNNs,
Transformers, & LLMs.

Scikit learn, Pyspark, Langchain, Pandas, Numpy, Seaborn

My Experience

Dec 2023 – Present

e& Enterprise

Senior Data Scientist

– Spearheaded a Customer 360 Dashboard that illustrates the
entire history of the customer, the current KPIs for each integrated data source, and additional AI use cases that improves the service and relationship with the customer. One of the AI use cases is an Opportunity Winning Probability model with an accuracy of 80+% and an F1-score of 0.83
-Lead an internal business costs analysis and constructed a
comprehensive dashboard with precise improvements which
accounted for potential cost savings of 50 to 80 million AED
yearly.
-Conducted a Call Centre Analysis for a critical customer. This was comprised of several dashboards that showcased agent
performance, utilization issues, and possible improvements
along with a resource demand forecasting ML model. This project reduced the Call Abandonment Rate by 74%.
-Constructed a Machine Learning model that predicted the
probability of a parking sensor being empty on a future day and
hour with an accuracy of 80%+. This reduced the cost of failed
maintenance activities by an estimated 50%.
-Implemented a live automated dashboard that detected battery,
charging, and measurements issues for noise sensors. This led to
sensor placement restructuring and intervention by the sensor
vendor

Aug 2020- Dec 2023

DataScrutineer

Data Scientist

Helped several companies in the US and UK make data-driven decisions that reduced costs, optimized workflows, and solved problems.

– Implemented predictive maintenance using machine learning in water filtration pipes for a US water filtration and delivery company, reducing maintenance costs by an estimated 20-30%.

– Developed a 120-hour structured deep learning curriculum for a UK company course, guiding learners from foundational neural networks to advanced topics like CNNs, RNNs, GANs, and transformers using 3 hands-on projects in image classification, sentiment analysis, and speech recognition.

-Developed complex Image Processing Pipelines for a German Entity to efficiently analyze and classify entities in multiple images.

Machine Learning

I have experience implementing machine learning use cases like anomaly detection, classification, regression, clustering, predictive maintenance, and time-series forecasting.

Deep Learning

I am also experienced with implementing Deep Learning use cases using models like Dense Neural Networks, CNNs, RNNs, LLMs and other models. These include Computer Vision and NLP use cases.

Data Analytics

I am also proficient in analyzing data using programming languages, like Python and R, and constructing dashboards using Tableau and Power Bi to derive insights from operational and company data.

I help companies utilize data and AI to reduce costs, optimize workflows, and solve problems. I specialize in the IoT, Healthcare, and Education industries.

Some examples include:

Predictive Maintenance using Machine Learning – Water industry:

I implemented predictive maintenance using machine learning in water filtration pipes for a water filtration and delivery company, reducing maintenance costs by an estimated 20-30%. I achieved this by conducting data analysis, recommending tailored machine learning models, and implementing refined sensor data optimizations, adjusted data collection frequency, and enhanced maintenance scheduling. The result is a more efficient and cost-effective system.

Deep Learning Curriculum:

I developed a 120-hour structured deep learning curriculum for a company course, guiding learners from foundational neural networks to advanced topics like CNNs, RNNs, GANs, and transformers. Through 3 hands-on projects in image classification, sentiment analysis, and speech recognition, learners achieved practical mastery with real datasets. Proficiency in TensorFlow, a prominent deep learning framework, rounded out their skill set, ensuring a seamless transition to impactful real-world applications.