Tabarek Ayad

Conduct Model Risk Management (MRM) activities to ensure models are accurate, compliant, and regulatory-ready.
Develop and validate models using statistical and machine learning techniques using Python, R, SAS, SQL, or Scala/Spark.
Perform constraint purification, benchmarking, MoDeVa validation tests, Concord/ValOps, and comparative analysis for credit scoring models.
Collaborate with experts and present insights to stakeholders.
Stay current with regulatory frameworks and risk trends.

Built hierarchy-based training data (labeling) for AI histology image segmentation.
Segmented and quantified cell types efficiently using QuPath and PyTorch.
Worked on histology cell classification using CNN with PyTorch.

Worked as a consultant expert to provide industry expertise and knowledge in the Data Analytics field.
Developed the certification domain and exam objectives.
Wrote exam questions in the Item Writing phase.
Reviewed and evaluated the previous version of the certification exam, and made a notable change.

Assisted in developing, setting the basis, and running the first in-company data models.
Generated ad-hoc and periodic statistical reports from the Oracle database.
Ensured data integrity by carrying out sanity checks and conducting necessary investigations.

Delivered classes as an instructor of the cohort of Data Analytics using Excel and Machine Learning Microwork.
Generated guides and training materials for image segmentation and annotation of datasets.
Delivered training and Standard Operating Procedures (SOPs) before and during project deployment.

Imported Call Detail Records (CDRs) data into the database.
Collected CDR files that contain data from the mobile communication system.
Generated ad-hoc and periodic reports from the Oracle database.