About me
I connect analytical thinking with hands-on engineering.
My work spans machine-learning research, business intelligence and application development. At Deloitte Morocco, I developed a phishing-detection prototype. At Tractafric Equipment, I worked on data architecture and reporting across operational functions. Through research and independent projects, I’ve also built tools spanning mobile applications, IoT and assistive technology.
Experience
Experience across analytics, machine learning, software engineering and applied research.
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Oct 2025 - Aug 2026
Data Analyst - Optorg Group / Tractafric Equipment
Designed a multi-source data architecture across ERP, CRM, after-sales, telematics, finance and maintenance. Built Power BI and DAX dashboards for margins, costs, revenue and the sales funnel, reducing recurring reporting preparation by up to 60%.
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Jun - Aug 2024
Cybersecurity & AI Intern - Deloitte Morocco
Developed a phishing-detection proof of concept with a browser extension and Flask inference API. Evaluated traditional classifiers and a fine-tuned DistilBERT model, which achieved 98.1% F1 on the held-out test set.
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Jan - Jun 2023
Software Engineer - Ministry of Health and Social Protection
Developed an internal HR platform with role-based access, workflow automation and structured employee data. It digitized six form types for 120 employees, replacing manual paper-based processes.
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Research & AI
Applied ML, IoT & assistive technology
Co-authored a peer-reviewed irrigation-optimization paper and deployed its models through a Flask API and Flutter app. Also built a voice-controlled Raspberry Pi assistive device combining face recognition, OCR, VLM scene description and a distributed edge-server pipeline.
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Product
PeerFit - Social sports events platform
Built, deployed and grew a geo-based sports events app with React Native, Node.js and PostgreSQL to 500+ active users and 300+ events, with product analytics for engagement and retention.
How I Approach Engineering
Understand the problem, test an approach and build something useful around the result.
01. Understand the problem
Clarify the users, the operational context and the constraints. Define what success would look like before choosing a model, tool or architecture.
02. Design the right workflow
I map the user journey, the data and the integration points before choosing the technology, whether that is a website, model, dashboard or automation.
03. Build and validate
The system is tested against the agreed scenario, with the people who will use it. You validate the result before the final delivery, not after it.
04. Document and improve
Document the implementation, communicate its limitations and make the system easier for others to use, maintain and improve.
A practical profile: systems that connect business outcomes with engineering depth.
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Shipped projects
Core specialties
Academic & professional institutions
Building since
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Direct point of contact
Frequently
Asked Questions
Straight answers about scope, delivery and
the way I work.
Seeking full-time roles and internships in AI/ML engineering, data science, and data engineering or analytics.
Yes. I take on selected projects in AI applications, data and BI, workflow automation and custom web platforms. We start by defining the users, constraints and delivery scope.
Yes. I work remotely across Morocco and France, with clear milestones, shared access and direct communication throughout the project.