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Nelly TraoreNT

Nelly Traore

Machine Learning Engineer

€780/day
Paris, FR
8-15 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Nelly

Hello,

Welcome to my profile. I am a Machine Learning Engineer and I have been working on machine learning topics from data collection to production deployment. My key skills are:

• Analysis and definition of needs, scoping of Machine Learning projects
• Data collection, preparation, and transformation
• Exploratory analyses
• Development of predictive/explanatory models
• Deployment of models in production
• Realization of POCs

Do not hesitate to contact me so we can discuss your project.

Sincerely,

Nelly Traore
  • French

    Native or bilingual

  • English

    Native or bilingual

Can work on-site
Paris (up to 50km)

Experience

  • Inata Intl - 3DS Informatique et Sécurité
    Lead Data Scientist and MLOps
    May 2024 - October 2024 (5 months)
    Abidjan, Côte d’Ivoire
    **Context**: Scoping and initialization phases of the project to develop an AI-assisted management application.



    **Project**: Creation of a RAG with the gemma2 model (Proof of Concept) for a report creation assistant application, with AI assistance.



    **Responsibilities**:

    • Requirements gathering and scoping
    • Definition of data collection needs to successfully complete the project
    • Definition of the technical architecture of the ML system
    • Development of the RAG with the gemma2 model
    • Deployment of the PoC (alpha version) to allow business experts to conduct initial tests of the tool

    **Technical Stack**: Python, PostgreSQL (pgvector), MLflow, OpenLLM, Ollama, LangChain, Git, GitHub, Azure VM, FastAPI, Docker

    Python PostgreSQL PGVector MLflow OpenLLM Ollama Langchain Git GitHub Microsoft Azure FastAPI docker-compose Docker
  • LVMH
    Machine Learning Engineer
    LUXURY GOODS
    March 2021 - December 2023 (2 years and 9 months)
    Paris, France
    **Context**: Within the RIMOWA entity of the LVMH Group, the objective was to contribute to the execution of the Business and IT Data Engineering roadmaps.



    **Project #1 Machine Learning Engineer**: Implementation and deployment of Machine Learning (ML) models, performing ad-hoc statistical analyses to extract useful business insights.



    **Responsibilities**:

    • Implement a score to detect customers with high repurchase potential
    • Implement a product recommendation system
    • Industrialize the new customer segmentation model
    • Deploy models in production and implement automated monitoring
    • Administer Dataiku machines
    • Perform ad-hoc statistical analyses
    • Strengthen IT teams in monitoring the data quality of the CRM database

    -------------------

    **Project #2 Data Engineer**: Within the IT Data Engineering team, explore and develop tools to evolve certain aspects of the platform.



    **Responsibilities**:

    • Lead the testing phase of the customer SI refactoring project to GCP cloud, in terms of migration and data quality
    • Support the Business Data team in accelerating cross-functional projects and AI use cases
    • Develop a Cloud Function to process and share anonymized data with another cloud provider
    • POC and V1 deployment of Google Dataplex to monitor data quality in ingestion and processing pipelines
    • POC on setting up Cloud Composer to centralize the orchestration of all data processing pipeline jobs

    **Technical Stack**: Dataiku DSS, Python, JIRA, BigQuery, Google Cloud Storage, Cloud Functions, Cloud PubSub, Terraform, Dataform, GCP Dataplex, Cloud Composer, Airflow, Cloud Build, Git, GitHub

    Dataiku Python Big Query Google Cloud Storage Google Cloud Functions Google Pub/Sub Terraform Google Cloud Platform Dataplex Google Composer Airflow Salesforce Atlassian JIRA Git GitHub
  • M2I Formation
    Data Scientist Trainer
    EDUCATION AND E-LEARNING
    November 2020 - February 2021 (3 months)
    Paris, France
    **Context**: Training future Data Analysts in the use of Python and its packages for data analysis, statistical studies, and Machine Learning.



    **Responsibilities**:

    • Discover and use Jupyter Notebook and widgets to create interactive dashboards
    • Review basic statistical concepts for data analysis
    • Explain the functioning of libraries used in data analysis (Numpy, Scipy, Pandas)
    • Explain the functioning of the Matplotlib library for Data Visualization
    • Explain the functioning of the Scikit-learn library for Machine Learning
    • Set up practical workshops for each section.

    **Technical Stack**: Python (Numpy, Scipy, Pandas, Matplotlib, Scikit-learn), Jupyter notebook

    Python Jupyter Numpy Pandas Scikit-learn Matplotlib Scipy

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Education

  • Master
    University Paris-Est Créteil
    2016
    Econométrie et Statistiques Appliquées

Certifications

Skill set (53)

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