Rami Sabeur

I worked as a freelance for Airbus, Marseille Hospital, and Burger King

Achievements:

• Conducted a statistical study for Airbus Helicopters to estimate the number of non-conforming helicopter parts.
• Developed a convolutional neural network model for handwritten text recognition (Airbus Palantir Foundry). Train the data with Palantir AIP Migrate the data from SAP to Palantir with HyperAuto, train the data with Palantir AIP. Integration of this model in a UiPath robot.
• Developed a Natural Language Processing (NLP) and Optical Character Recognition (OCR) model to determine whether a technical document is confidential (Airbus). Check if the visual information gathered match with the classification in SAP.
• Developed a Big Data solution that centralizes all data from a service, cleans, processes the data, and sends it to the right people for their activities (Airbus Palantir Foundry).
• Created an AI solution for predicting the severity of incidents for the Burger King group.
• Developed a computer ai solution to automate the antibiogram test. An antibiogram is a test used to determine the sensitivity of a bacterium to different antibiotics, helping guide the selection of antibiotic treatment.

I was headhunted by Alten to become a consultant for Airbus. In this role, I continue my previous activities, train new engineers, and develop Alten's data science business. I have taken on new responsibilities:

• Training data scientists in big data (Apache Spark).
• Developing in Python and PySpark on Palantir Foundry.
• Implementing a tool that provides real-time storage policy advice for a set of product references. This involves calculating the variance in delivery delay and the demanded quantity of the product. Both risks are considered in the calculation of safety stock.
• Creating an OCR model to classify different types of engineering documents.
• Establishing a predictive maintenance model for helicopter parts referred to as "critical parts."

Data scientist, responsible for digitising the process of checking the conformity of engineering plans and documents.
Responsible for setting up robots in the Airbus Helicopter design department.

• Quality audit of Airbus Helicopters' archiving process. The audit enabled the process to be reduced by one FTE and its quality to be improved.
• Setting up statistical indicators to detect the root causes of data quality problems in the archive database.
• Project architect: UiPath robot. Airbus aims to have 30 robots in place by the end of the year. I'm in charge of setting up 3 of them, and monitoring, maintaining and upgrading them. (Project owner) Project completed: 80% reduction in the cost of the conformity control service for engineering documents.
• Calculation of the full cost of the archiving activity in order to set up work units instead of work packages.
• Implementation of an A.I. model to detect logos and keywords on documents.
• Creation on Palantir, a big data platform, of a python/pyspark code on the cloud, which allows the monitoring of UiPath robots.
• Implementation of a predictive model of engineering document volume on Skywise Palantir. Holt winters time series.

Data Scientist, responsible for the digitalization of the compliance control process for engineering plans and documents. In charge of implementing robots within the Airbus Helicopters design department.

• Conducted a quality audit of the Airbus Helicopters archiving process. The audit resulted in a reduction of one FTE in the process and improved its quality.
• Established statistical indicators to identify the root causes of data quality issues in the archive database.
• Project Architect for UiPath Robot. Airbus aims to implement 30 robots by the end of the year. I am tasked with implementing 3 of them, ensuring their monitoring, maintenance, and evolution. (Project owner) Completed project: achieved an 80% reduction in the cost of the engineering document compliance control service. Calculated the full cost of the archiving activity to implement work units instead of work packages.
• Developed an AI model to detect logos and keywords on documents.
• Created a big data platform on Palantir with a Python/PySpark code on the cloud, enabling the monitoring of UiPath robots. Implemented a predictive model for the volume of engineering documents on Skywise Palantir using Holt-Winters time series.

• Define the digitalization strategy
• Migrate the data to S.A.P
• Create automatic data quality analytics with Python and Apache Spark
• Create a favorable environment for setting up predictive models with A.I
• Benchmark k.p.i
• Statistical study