I am a data scientist with experience in supply chain optimization across the automotive
industry, transport industry, and sport retail. I build analyticak products, optimization
models, and decision tools that connect business strategy with operational performance
Abdelrahman Lemmouchi
Data Scientist • Optimization Engineer
Forecasting, Computer Vision, GenAI, Machine Learning, experimentation, modeling, and interpretable analytics
Planning, flows, stocks, constraints, capacity usage, and better trade-offs.
From raw data to operational dashboards and scalable recommandations.
about me
I am a data scientist with experiences in supply chain optimization, working on problems
where performance depends on the quality of both data and decisions. My background enables
me to translate industrial and logistical complexity into structured models, predictive
insights, and optimization strategies.
Across the automobile industry, transport industry, and sport retail, I have contributed as
an optimization engineer and data scientist to improve processes, support operational
planning, and strengthen decision-making. I enjoy creating solutions that are rigorous,
usable, and aligned with business constraints.
What motivates me the most is solving practical challenges with analytical depth : from
network and flows optimization to forecasting, scenario analysis, and AI driven decision
support. I believe the best data products are not only technically strong but also trusted
by the teams who use them.
Core strenghts
Strong analytical thinking for operational and strategic decision problems
Supply chain perspective with experience across multiple sectors
Curiosity for AI, experimentations, and continuous improvement
Experiences
Build & Deploy predictive and analytics solutions
Building and deployment of a predictive model to detect employee churn in factory (XGBoost, Survival Analysis)
Building and local deployment of computer vision model to assess manufacturing quality on bumpers (Yolov8, RD++)
Creation of a GenAI powered chatbot to query purchasing contracts in natural language (RAG architecture, LLM, Copilot Studio)
Industrial operations, planning, and process optimization
Optimization of transport network of finished vehicles using Operation Research (NetworkX, OR-Tools)
Forecasting of finished vehicles manufacturing - yearly, monthly, weekly mesh
Planning optimization of transport schemes - model, country level
end-to-end supply chain inventory optimization - warehouse, store levels
Statistical disaggregation of weekly forecast to daily forecast
Sales, stock, leadtime statistical analysis
Optimization of safety stock with leadtime and error forecast volatility
Industrialization of the solution using Databricks, dbt
skills
beyond work
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