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Hao Li

data science, machine learning, data strategy

En télétravail depuis Paris

  • 48.858705
  • 2.342865
Proposer une mission La mission ne démarrera que si vous acceptez le devis de Hao.
Proposer une mission La mission ne démarrera que si vous acceptez le devis de Hao.

Localisation et déplacement

Localisation
Paris, France
Télétravail
Effectue ses missions majoritairement à distance

Préférences

Durée de mission
  • ≤ 1 semaine
  • ≤ 1 mois
Secteur d'activité
  • Aéronautique & aérospatiale
  • Agroalimentaire
  • Architecture & urbanisme
  • Arts & artisanat
  • Automobile
+38 autres
Taille d'entreprise
  • 1 personne
  • 2 - 10 personnes
  • 11 - 49 personnes
  • 50 - 249 personnes
  • 250 - 999 personnes
+2 autres

Vérifications

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Langues

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Catégories

Compétences (7)

Hao en quelques mots

With deep understanding of data science and machine learning and 9 years' corresponding experience (4 years in R&D, 2 years at IBM, 3 years at Sodexo), I have rich experience of each stage of Data and AI project (POC, Scoping, MVM, MVP, Industrialization) in different sectors (bank, restaurant services and facilities management, retails, energy, aeronautique, pharmacie). My various project oriented and client-facing working experience makes me not only able to fullfill technical work but also enable me to play the role as project manager and data translator. I hold a PhD degree with qualified competence and skills in innovation and R&D work(four 1st author publications on top world class scientific journals). I speak fluently french, english and chinese.

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Expériences

SODEXO - Sodexo

Restauration

Senior data scientist

Issy-les-Moulineaux, France

juin 2020 - novembre 2022 (2 ans et 5 mois)

Lead data scientist on retail, pricing projects:
- Dynamic pricing for corporate France, US
- New food model of digital transformation in China
- AI asset initiation and developement

  • Participate the whole project life cycle: Project framing, MVM(minimum viable model), MVP(minimum viable product), Industrialization
  • In charge of conception and on boarding of data driven solution (BI, AI) to address business needs and pain point
  • Coach data scientists resources on retail, pricing projects

Main contributor of NLP asset of Sodexo Data Factory:
- Standard pipeline for NLP tasks include sentiment analysis, topics extraction, topics classification (Bert, GPT-3 etc)
Pricing NLP Fuzzy Matching segmentation MLOps Python Microsoft Azure

IBM France

High tech

Data Scientist & Machine Learning Engineer

Bois-Colombes, France

juin 2018 - juin 2020 (2 ans)

1. Airbus Skywise project: predictive maintenance and anomaly detection by Machine Learning.

- Creation of data pipeline: massive timeseries data treatment and analysis by using Pyspark
- Creation of machine learning pipeline: models (deep learning: Autoencoder) development and hyper-parameters tuning (Bayesian Optimization)
- Deployment of data pipeline and machine learning pipeline for real time prediction to provide KPI in dashboard for anomaly detection

Technical environment: Pyspark, Tensorflow, Keras, Amazon AWS, Palantir

2. Ipsen & Roche: Prediction of adverse event of medications for Pancreas cancer; Prediction of treatment switch in diabetes type-2 patient journey.

- Defining hypothesis and cohort
- Feature engineering: cleaning data and creation of data model
- Advanced analytics: demographics analysis
- Creation of machine learning pipeline: deep learning model (LSTM) to predict time series event (adverse event); Cox analysis model (diabetes)
- Creating causal inference model for causality analysis and for eliminating bias in data

Technical environment: Jupyter notebook, Pycharm, Tensorflow, Keras, IBM explorys, SQL, Docker

3. POC for Nissan: Artificial intelligence solution for guided diagnostic of vehicles (Natural Language Processing NLP).

- Transformation of unstructured data (customer complains e-ticket) to structured data (NLP text analysis)
- Feature engineering: cleaning and standardising data
- Machine learning modelling: creating prediction models to precisely classify e-ticket.

Technical environment: Jupyter notebook

4. Compliance Watson for financial services of Crédit Mutuel: fraud detection and investigation of abnormal transactions against fraud and terrorist activities; customers retention.

-Feature engineering: cleaning, generation and exploitation of data for investigation
-Advanced analytics: data analysis
-Data modelling and AI modelling: creation of data model and machine learning prediction models.
Technical environment: Jupyter Notebook, SPSS, SQL, Watson Studio
Python Deep Learning Data Analysis Data visualisation AWS Microsoft Azure

Ecole Centrale de Lyon

Centres de recherche

Researcher

Écully, France

juin 2017 - mai 2018 (11 mois)

Conception and development of advanced model to predict high frequency acoustic and vibration effect in automobile and airplane by using historical data.

In charge of coordinating two R&D teams between Ecole Centrale de Lyon and Insa Lyon.
Innovation Data Modeling Mathématiques Algorithmes LaTeX

Université Paris Saclay

Centres de recherche

Researcher

Cachan, France

février 2014 - mars 2017 (3 ans)

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Recommandations externes

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Formations

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Certifications 

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