Ministry-recognized founder
Auralytics AI was recognized as an innovative project by Algeria's Ministry of Knowledge Economy and Startups.
Data Scientist · Applied ML
Imed Eddine Aouidane
I bridge raw data and business decisions through statistical analysis and machine learning.
Master's-trained data scientist building computer vision, forecasting, and analytics systems with honest evaluation, practical interfaces, and the statistical discipline to turn messy data into facts a business can act on.
112k+
medical images used in X-ray modeling
DSIP '26
data science intern at Djezzy telecom
WMF 2025
AI innovation conference, Bologna
Available for data science roles, research collaborations, and selected freelance projects.
Djezzy · DSIP
Telecom data science, 2026
Clinical AI
Hospital workflow project
01 — about
About Me
I'm a Data Scientist from Algeria with a Master's in Data Science for Economics and Business. I like the parts of data science where research discipline meets shipping: clean data, honest evaluation, useful interfaces, and a clear reason for the model to exist.
My work spans telecom, healthcare, oil and gas, and e-commerce. Right now I'm a data science intern at Djezzy through the DSIP program, doing deep exploratory data analysis on large-scale telecom data. Recent projects include a cardiology assistant for a hospital workflow, chest X-ray classification pipelines, climate forecasting experiments, and client-facing analytics applications.
What ties it together: I translate raw, messy data into statistical evidence that non-technical stakeholders can actually use to make decisions.
- Python, R, SQL & Git workflows
- pandas, NumPy & statsmodels
- PyTorch, TensorFlow & scikit-learn
- ARDL, ECM, ARIMA & forecasting
- FastAPI, Streamlit & Power BI
- PostgreSQL & data pipelines
02 — skills
Skills & Expertise
A practical stack for applied data science: statistics, models, data plumbing, and the communication needed to turn results into decisions.
Statistical Analysis
- Exploratory data analysis (EDA)
- Hypothesis testing and inference
- Econometrics: ARDL, ECM, cointegration
- Diagnostics and model validation
Machine Learning
- Deep learning pipelines
- Model evaluation and diagnostics
- Feature engineering
- Production-minded experimentation
Computer Vision
- Faster R-CNN, YOLO, ResNet
- Medical image classification
- Object detection and surveillance
- Grad-CAM and explainability
Forecasting
- ARIMA, SARIMA and ETS
- XGBoost and LSTM comparisons
- Stability and residual diagnostics
- Uncertainty quantification
Data Systems
- PostgreSQL and normalized schemas
- Web scraping and ETL
- FastAPI and Streamlit apps
- Notion and Telegram integrations
Delivery
- Client discovery and scoping
- Clear technical communication
- Independent project lifecycle
- Documentation and iteration
Research and recognition
Evidence first. Demos second.
My strongest projects pair statistical discipline with practical engineering: causal modeling for AI revenue impact, clinical decision support, medical computer vision, and forecasting for climate risk signals.
Master's thesis with econometrics
Used ARDL and ECM methods to model the link between AI adoption and NVIDIA financial performance.
International AI exposure
Presented and networked at We Make Future 2025 in Bologna with researchers and industry teams.
03 — work
Selected Systems & Research
A curated set of projects that show range across research, deployed systems, client-facing analytics, and product thinking.
Showing all selected work.
Telecom Data Science · In Progress
Djezzy — Large-Scale Telecom EDA (DSIP Program)
Python / pandas / NumPy / seaborn / SQL / statistical analysis
Ongoing project at Djezzy, one of Algeria's leading mobile operators, as part of the DSIP internship program. I own the exploratory data analysis phase on large-scale telecom datasets: data quality profiling, distribution and correlation analysis, segmentation hypotheses, and framing statistical findings as KPIs the business can act on.
Statistical EDA on industry-scale data
Raw data translated into business insights
Scope described at a methodology level — business data and findings stay confidential.
Health AI
Cardiopulmonary Classification from Chest X-rays
Python / PyTorch / ResNet-50 / OpenCV / Grad-CAM
Built a multi-label deep learning pipeline for cardiomegaly, pneumonia, and pleural effusion detection using the NIH Chest X-ray dataset with 112,000+ images and 14 disease labels.
AUC-ROC and precision-recall evaluation
Grad-CAM model attention visualizations
Clinical Assistant
CardioBot - AI Cardiology Assistant
Python / Telegram Bot / Claude API / Notion API
Designed a Telegram-based assistant for a cardiologist at CHU Mustapha Hospital, enabling natural-language access to structured patient records, medication notes, and clinical summaries.
Designed for active hospital workflow
Real-time retrieval from structured records
Master's Thesis
NVIDIA AI Revenue Impact Study
R / ARDL / ECM / ARIMA / Econometrics
Modeled the causal relationship between AI adoption and NVIDIA revenue using quarterly financial data from 2015-2024, with ARDL bounds testing and error-correction modeling.
F-statistic 8.47, p < 0.001
~67% quarterly adjustment speed
Climate ML
Climate Forecasting & Extreme Weather Detection
Python / SARIMA / XGBoost / LSTM / pandas
Compared statistical and ML forecasting methods on daily climate data to predict temperature trends and flag extreme heat events using engineered lag and interaction features.
SARIMA, XGBoost and LSTM comparison
Heatwave anomaly detection module
Computer Vision
Real-Time Multi-Camera Surveillance System
PyTorch / TorchVision / PostgreSQL / Flask
Built a GPU-optimized Faster R-CNN inference pipeline with multi-threaded camera management, PostgreSQL event logging, and automated alert generation.
Sub-200ms end-to-end latency target
Production-style monitoring architecture
Client Data Product
E-commerce Competitor Intelligence
Python / PostgreSQL / Selenium / Power BI
Scraped and normalized 2,500+ product records from a cosmetics e-commerce competitor, enabling structured market positioning and competitor benchmarking.
Predictive Analytics
Oil & Gas Predictive Analytics Platform
Python / Streamlit / scikit-learn / seaborn
Developed a Streamlit application for bottom-hole pressure prediction with EDA, model performance reporting, and client-ready export workflows.
80% train/test accuracy reported
Automated report generation
Founder Project
Auralytics AI Platform
OpenAI Whisper / NLP / Python / FastAPI
Founded and built an AI meeting platform with real-time transcription, speaker diarization, summarization, secure authentication, and data workflows.
Ministry Recognized
Brand Case
Creative Venture
Medy Wear Brand Identity
Brand Strategy / Logo Design / Packaging / Apparel
A separate creative venture showing visual direction, brand building, and product taste. It supports the portfolio without competing with the main ML narrative.
04 — journey
Experience, Education & Recognition
2026 - Present
Data Science Intern @ Djezzy - DSIP Program
Selected for Djezzy's DSIP internship program. Working on exploratory data analysis of large-scale telecom data: data quality profiling, statistical analysis, and turning raw data into business-facing insights. Project details remain confidential.
2024 - Present
Freelance Data Scientist
Scope client problems, build predictive and automation systems, explain findings clearly, and manage projects from briefing through delivery.
Jun 2025
Master's Degree - Data Science for Economics & Business
Graduate School of Economics, Oran. Thesis focused on ARDL and ECM econometric frameworks for modeling AI adoption and financial performance.
Jun 2025
We Make Future 2025 - Bologna, Italy
Represented Algeria's Graduate School of Economics at an international AI and innovation conference, engaging with researchers and industry teams.
Feb - Apr 2025
Data Analyst Intern @ MDM Hasnaoui
Prepared industrial data for predictive use cases, connected production data with KPIs, and diagnosed data quality issues before modeling.
Dec 2023
Data Analyst Intern @ LITMED PRO
Analyzed and visualized patient-level healthcare datasets, supported process optimization, and cleaned structured medical records for exploratory analysis.
Get In Touch
I'm available for data science roles, research collaborations, and selected freelance work in telecom, health, climate, forecasting, and data systems.