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Exemple de missions de Nora,
Data Scientist freelance

• Data Scientist / Lead Data Scientist

  Technip Energies (Digital Factory) Nanterre
  Jan 2022 - aujourd'hui

  Leading a team of 3 data scientists in an international
  environment.
  Working on multiple topics (GenAI, Computer Vision, OCR,
  NLP, Classification…) with different inputs (videos, images,
  PDFs and Tabular Data).
  Deploying different solutions (ex: Kubernetes clusters, azure
  apps..).
  Co-presenter in “The Big Data & AI Paris congress” for its
  12th edition (200 participants).
  6 months of platform training/comparison, including: Azure
  ML studio, Dataiku and RapidMiner.

• Data Scientist / Lead Data scientist

  Technip energies
  Jan 2022 - aujourd'hui

  Mission Description:
  I was leading a team of 2 to three data scientists depending on the number of current project. I worked on pultople
  subjects:
  ▪ Cost estimation: regression task.
  ▪ Text description classification: NLP task
  ▪ Defects recognition: computer vision task.
  ▪ Building digital twins
  ▪ Creating a safety camera system.

  Tools: Azure ML, Dataiku and RapidMiner platforms, Python, Pytorch, Tensorflow, Sklearn, OpenCV, Pillow, LabelImg, powerPoint.

• Data Scientist

  Eurailscout France - SNCF Paris
  Jan 2021 - Jan 2021

  Eurailscout France - SNCF Paris
  As part of computer vision project "Automated processing of
  track defects based on neural networks" in conjunction with
  SNCF partner, these points were covered:
  Improved current solution and performance evaluation.
  Prepared and implemented industrialization process.
  Developed new services for the detection of vegetation and
  recognition of writings on rail images.

• Data Scientist

  Eurailscout France (SNCF)
  Jan 2021 - Jan 2022

  Mission Description:
  As part of computer vision project "Automated processing of track defects based on neural networks" in conjunction with
  SNCF partner, these points were covered:
  ▪ Recognition on rail images.
  ▪ Evaluation of the performance of the results obtained (methods, processes).
  ▪ Preparation and implementation of industrialization process.
  ▪ Put in place an active learning system for continuous learning.
  ▪ Development of new services for the detection of vegetation and recognition of writings on rail images.

  Tools: Agile (Scrum), Azure ML(VM), Python, Pytorch, Tensorflow, Sklearn, OpenCV, Pillow, Tensorboard, Power BI, VSCode, GIT, LabelImg, latex, powerPoint.

• Data Scientist

  Sercel (CGG Group)
  Jan 2019 - Jan 2020

  Mission Description:
  Design and implement a train detection system based on seismic signals using computer vision algorithms. In particular,
  the project responds to the following tasks:
  ▪ Track detection
  ▪ Detection and separation of trains.
  ▪ Detection of square wheels.
  Achievements:
  ▪ Data preparation: collect data, clean data, analyze signal, label data and convert signal into images.
  ▪ Bibliographic research, state of the art.
  ▪ Development, implementation and industrialization of the solutions.
  ▪ Agile work (SCRUM)
  ▪ Drafting of a final report.

  Tools: Python, Pytorch, Tensorflow, Sklearn, MLOps, OpenCV, Pillow, Tensorboard, Power BI, VSCode, GIT, LabelImg, latex,powerPoint.

• Data Scientist - Internship

  Lip6
  Jan 2018 - Jan 2018

  Mission Description:
  As part of the CLEF 2018 conference, the topic was “the early detection of signs of anorexia” using text mining and
  machine learning algorithms:
  ▪ State of the art of text classification methods.
  ▪ Data pre-processing: Data cleaning, selection of relevant characteristics, vector representation of texts.
  ▪ Application of text mining methods (TF-IDF, Bag of Word, embedding) in order to obtain the vector representations
  of the different words that make up the input texts.
  ▪ Use of deep learning algorithms (LSTM, GRU, RNN)

  Tools: Python, Sklearn , NLP, Numpy,NLTK,Eclipse, GIT, Power point, latex