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Rania A.RA

Rania A.

Machine Learning Engineer and Data Scientist, PhD

€550/day
Paris, FR
3-7 years
Data Science
Machine Learning
Python
MLOps
Time Series

Average response time: 4 hours

Freelancer profile translated to English.
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About Rania

Senior ML Engineer with a PhD in Artificial Intelligence and 5+ years of experience in end-to-end ML production. I industrialize Python models from A to Z: from prototype to supervised deployment, with full MLOps (monitoring, drift detection, versioning, registry).
Accustomed to demanding industrial environments, I naturally collaborate with architects, data engineers, and Product Managers in Agile/Scrum mode. My pipelines are modular, reproducible, auditable, and my models remain performant over time (zero regression in production).

What I bring:

- Industrialization of ML models and ELT/ETL pipelines in clean Python (Clean Code, unit tests, CI/CD).

- End-to-end MLOps: MLflow, drift monitoring, automated retraining, Grafana.

- Cloud deployment (Azure, AWS) via Docker and GitHub Actions.

- Real-time inference < 500ms on IoT sensor streams.

- Integration of LLMs and generative AI to enrich business workflows and automate analysis.

- 4 peer-reviewed IEEE & IFAC publications

- Bilingual FR/EN

Available ASAP · 5 days/week · Remote or on-site France
Automotive OEM
Automotive supplier
Energy and Electricity
Electrical industry
Plant and Machinery

  • French

    Native or bilingual

  • English

    Fluent

Can work on-site
Paris (up to 50km), France (up to 10km), Paris (up to 50km), Toulouse (up to 50km), Marseille (up to 50km)

Experience

  • LIS Lab et Predict
    Machine Learning Engineer: Industrial REST API for Time-Series Processing and Validation
    ENERGY AND UTILITIES
    January 2025 - Today (1 year and 5 months)
    Marseille, France
    Design and industrialization of a complete data pipeline for automatic detection and qualification of test sequences on multi-sensor data (time series).
    What I delivered:

    Modular and reproducible ELT pipeline in Python: production-ready architecture
    Expert system for detecting and classifying sequences (stable/unstable) on real-time streams
    Industrial REST API (Python · Flask) with client/server JSON exchange
    Docker deployment with formal testing protocol and auditable results
    Exploration of LLM approaches to automate result interpretation and interaction with analytical outputs

    Stack: Python · Pandas · Flask · Docker · REST APIs · Time-Series · CI/CD · LLM Integration
    Docker Python Pandas LLM Scikit-learn
  • Telaqua (IoT & Smart Irrigation Startup)
    Machine Learning Engineer, PhD (Energy & IoT)
    ENERGY AND UTILITIES
    January 2022 - January 2025 (3 years)
    Marseille, France
    Complete industrialization of ML models in production for critical IoT use cases: battery life prediction and real-time predictive irrigation control.

    Measurable results:

    • 92% F1 Score in production on Li-ion battery end-of-life detection
    • +30% accuracy vs baseline thanks to hybrid clustering + regression models (RUL estimation)
    • < 500ms latency on real-time inference pipeline (sensor stream → scoring → alerts)

    What I delivered:

    - End-to-end MLOps cycle: acquisition → feature engineering → training → versioning (MLflow) → deployment → continuous monitoring (drift, data quality, automated retraining)
    - Dockerized ML APIs deployed at clients with CI/CD and scalable pipelines
    - Predictive control system integrated into an IoT irrigation platform
    - Close collaboration with software and data engineering teams (Agile/Scrum)
    - 4 peer-reviewed IEEE & IFAC publications on battery health modeling and predictive control

    Stack: Python · PyTorch · TensorFlow · Scikit-learn · XGBoost · MLflow · InfluxDB · Grafana · Docker · AWS · CI/CD · SHAP · REST APIs
    Docker Gitlab CI/CD Data Science Data Analysis SQL
  • Groupe Renault
    Validation & Test Engineer
    AUTOMOBILE
    January 2020 - August 2021 (1 year and 7 months)
    Guyancourt, France
    ▸ Automation of test suites in Python (MIL), high-frequency time-series analysis for anomaly detection.
    ▸ Work in a structured industrial environment (AUTOSAR) with cross-functional QA teams in Scrum/Jira.

    Stack: Python · Jira · Agile/Scrum · AUTOSAR · Embedded Systems
    Machine Learning Python Data Analysis Data Analysis Data Science
Check out Rania's experience

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Education

  • PhD in Data Science
    Aix-Marseille University - Laboratory of Informatics and Systems
    2025
    Doctorat en IA
  • Master's Degree
    IFP SCHOOL
    2019
    Master's degree
Check out Rania's education

Skill set

Deep Learning
Pandas
Data Visualization
TensorFlow
Git
Gitlab CI/CD
Scikit-learn
Data Analysis
Pytorch
Diagnostic
Microsoft Azure
LLM
Data Engineer
PySpark
FastAPI
Data Integration
CI/CD Management
Langchain
Extract, Transform, Load (ETL)
Azure Cloud
Apache Spark
PowerBI
Grafana
Generative AI
Clustering
Unsupervised Learning
Big Data
A/B Testing
Algorithms and Data Structures
Databases
Industrial AI
SQL
AI Product Management
Spark
Time Series Analysis and Forecasting
Time Series Forecasting
Explainability
SHAP
Monitoring
NLP
Matplotlib
Retrieval-Augmented Generation (RAG)
Predictive Analysis
Microsoft Excel
Docker

Categories