Badre Belabbess

Skills: Artificial Intelligence (AI) · IT Strategy · Business Strategy · Generative AI · LLM · AI Solutions · AI Coaching

AI Vision : • Spearhead tech sector by offering forward-thinking leadership, • Advise AI endeavors to ensure they remain at the forefront of technology. AI Strategy Design : • Craft and implement a bold AI roadmap, • Identify new avenues for AI tools implementations, • Direct the creation of AI systems and techniques. AI Solutions Design : • Work hand-in-hand with top executives to translate business use cases into impactful, market-ready offerings.

Data Infrastructure Strategy • Partnership with AWS & GCP for client projects delivery • Implement SLA levels and performance optimization processes • Build scalable and distributed infrastructure using a mix of frameworks Data Platform Architecture • Build batch & real time data pipelines • Design highly available distributed Machine Learning/Deep Learning systems • Implement business applications empowered by AI and big data capabilities Research and Development: • Artificial Intelligence Scientific research track record • Big Data Scientific research track record

Big Data & Cloud: • Build batch data pipelines based on Airflow • Improve cloud production set up based on AWS services • Architecture new CI/CD set up based on Docker and Kubernetes Artificial Intelligence: • Embetter machine learning models (XG Boost) performance • Ensure consistent results for new models release based on GPU processing • Investigate Multi-model endpoints based on containers technology

Artificial Intelligence: • Conceive AI strategies to go at scale • Design AI platforms empowered by big data systems accross all industries • Implement machine learning/deep learning algorithms for complex business needs • Manage large data science teams in agile environment Big Data: • Design state of art Big Data platforms with highly distributed processing • Maturity Assessments and data strategy design • Conceive end-to-end delivery process for critical big data projetcs • Manage large engineers teams in agile environment

Big Data: • Data Platforms at scale • Streaming Applications Artificial Intelligence: • AI projects end-to-end cycle • Deep learning solutions for complex business cases DevOps: • Deployment environments for big data applications • Distribution strategies for process optimization

Big Data: • Conceive Big Data platforms in a streaming environment using Apache Storm, Spark and Kafka • Build scalable and distributed infrastructure using a mix of frameworks • Analyze Media and social networks for information retrieval to contextualize singularities • Manage and set up deployment environment using Docker and Kubernetes Artificial Intelligence: • Design highly available distributed Machine Learning/Deep Learning systems • Implement business applications empowered by AI and big data capabilities • Optimize processing algorithms for multiple Research and Development: • Artificial Intelligence Scientific research track record • Big Data Scientific research track record

Modelization & Statistics: • Formalization & calibration of the White-hull model • Pricing of the different valuation adjustments using R • Statistical models (ACP, Regressions, Binomial Trees) using SAS • Capital measurements: probabilities calculations Machine learning algorithms using PYTHON: • Development/coding of forecasting methods (Random forests) • Creation of what if scenarios and back testing using supervised learning • Implementation of new algorithms, KNN, naïve Bayesian classification • Follow-up of FVA/CVA positions using C++ algorithms

Conference & College Lecture on financial instruments: • Pricing and valuation methods • Risk calculation, mathematical models • Regulation, Legislation, International legislation

Creation of Internal Control tools using PYTHON: • Mathematical Formalization of the methods • Creation of pricing/calculation libraries • Implementation of geometrical models Risk assessment and forecasting: • Implementation of risk weights using R statistical models • Establishment and follow-up of action plans: classification methods • Analysis of operational incidents declarations using Text Mining Participation in various works within MARK department: • Review of the operational processes and procedures • Development of reports for the managing divisions