- Work in all phases in the life-cycle of machine learning applications.
- Work with data scientists, application software engineers, program and product managers to deliver advanced analytic values to internal and external customers.
- Strong understanding of both classical ML and deep learning techniques.
- Experience with ML model evaluation and training techniques for deep neural networks.
- Expert skill level with Python, Pandas.
- Extensive experience with deploying complex systems to the cloud.
- Strong analytical and problem-solving skills .
- Possess a background in linear algebra, statistics, or multivariate calculus.
- Experience in one or more deep learning frameworks such as Tensorflow/Keras, or PyTorch.
- In-depth knowledge of one or more deep learning areas such as computer vision or Natural Language Processing (NLP)
- Strong analytic skills related to working with structured and unstructured datasets.
- Prior participation in data science competitions such as Kaggle, DrivenData, or CodaLab.
- Lead projects requiring data engineering solutions development.
- Education: Master's or PhD degree in Computer Science, Mathematics, Economics, or equivalent.
- Experience: 5+ year-experience including graduate or postgraduate research.
- Related skills:
- Data tools related to: data pipeline, data factory, data lake.
- AWS and GCP related ML services.
- RESTful API, Redis Cache.
- Python, SQL, R
- Personalization modelling, recommendations system, churn prediction, time series forecasting.
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