05/25/2024 updated


100 % available
Data Scientist
Villejuif, France
Only remote
Artificial IntelligenceApache AirflowAmadeus CRSAmazon Web ServicesInformation EngineeringWeb ScrapingPython (Programming Language)PostgreSQLMachine LearningMongoDBNumPyMicrosoft Power BITensorFlowSoftware EngineeringSQL Databases
Airflow, Amadeus, AWS, Artificial Intelligence Systems, Data pipeline, Data Pipelines, Deep learning, Docker, FastAPI, Flask, GIT, Heroku, data engineering, Jupyter Notebook, Machine Learning, Matplotlib, MongoDB, NumPy, Plotly, PostgreSQL, PowerBI, Prophet, PySpark, Python, PyTorch, Random Forest, SQL, Scikit-learn, Application Development, spaCy, TensorFlow, web application, web scraping, XGBoost
Languages
EnglishFluentFrenchBasic knowledge
Project history
* Business Objective: Enhanced the existing passenger traffic forecasting
process that predicts market shares and total revenues.
* Data preprocessing and analysis using PySpark and SQL.
* Supervised ML models such as Random Forest and CatBoost and model
explanation using SHAP.
process that predicts market shares and total revenues.
* Data preprocessing and analysis using PySpark and SQL.
* Supervised ML models such as Random Forest and CatBoost and model
explanation using SHAP.
* Business Objective: Build 'Price Prediction' regression model for
recommending quote price for their product wise at the line-item level.
* Data collection using web scraping.
* Data preparation, analysis, preprocessing and created visualizations.
* Developed ML models such as Decision Tree, Random Forest, boosting
algorithms and applied Hyperparameter tuning to optimize the model.
* Value Creation: Infosys won the Multi-Vendor Hackathon for "Request for
Proposal" Project
recommending quote price for their product wise at the line-item level.
* Data collection using web scraping.
* Data preparation, analysis, preprocessing and created visualizations.
* Developed ML models such as Decision Tree, Random Forest, boosting
algorithms and applied Hyperparameter tuning to optimize the model.
* Value Creation: Infosys won the Multi-Vendor Hackathon for "Request for
Proposal" Project
* Business Objective: Created 'Package Pricing' model for prediction of the
cost to hospitals.
* Developed a Classification model backed by Regression model and
clustering like Decision Tree, Random Forest, KNN, SVM, XGBoost
* Created a product for precautionary measure to understand if a data acquisition system is behaving as expected
or unusual and therefore seek the attention of data engineering team immediately to investigate and take
immediate actions i.e., developed univariate time series model to predict the amount of data required to be
acquired for multiple business process.
* Deployment of ML models using Docker and Flask
* Value Creation: The client reported getting 7% increase in revenue on launch of this innovative product in Q1 of
2019
cost to hospitals.
* Developed a Classification model backed by Regression model and
clustering like Decision Tree, Random Forest, KNN, SVM, XGBoost
* Created a product for precautionary measure to understand if a data acquisition system is behaving as expected
or unusual and therefore seek the attention of data engineering team immediately to investigate and take
immediate actions i.e., developed univariate time series model to predict the amount of data required to be
acquired for multiple business process.
* Deployment of ML models using Docker and Flask
* Value Creation: The client reported getting 7% increase in revenue on launch of this innovative product in Q1 of
2019