Data Scientist in charge of implementing and deploying deep learning models for fluorescence detection in images of microscope :
- Implementation of unsupervised models related to image segmentation
- Implementation of supervised models related to object detection in images
Data Scientist in charge of the implementation of models related to fraud detection, money laundering and terrorist financing :
- Detection of suspicious transactions,
- Detection of matching between customers and persons appearing on the politically
exposed persons or sanction/embargo lists,
- Segmentation of countries according to risk related to money laundering and terrorist financing.
Data Scientist in charge of the implementation and deployment of anomaly detection APIs for multidimensional, time series and text data :
- Implementation of unsupervised models :
- Implementation of supervised models for imbalanced data : cost-sensitive learning, resampling (under-sampling, over-sampling, SMOTE, etc…),
- Web APIs creation,
- Deployment on cloud
Lead Data Scientist in charge of identifying and implementing Machine/Deep learning use cases for the certification of counterparty metrics (CVA, CVAR, etc…) :
- Identification of Machine/Deep learning use cases
- Statistical analysis of daily variations in counterparty metrics,
- Supervised/ Unsupervised/Semi-supervised anomaly detection of intra-variations in counterparty metrics.
Data Scientist in charge of implementing deep learning models for image classification, image
segmentation, object detection in images :
- Data collection/ web scraping of data images,
- Implementation of image classification models,
- Implementation of object detection models,
- Implementation of image segmentation models.
- Deployment of models on cloud.
Data Scientist in charge of implementing and deploying machine learning models related to customer loyalty :
- Implementation of churn models (scoring models),
- Implementation of models for smart pricing,
- Deployment of models on cloud.