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9 592
Responsibilites:
* Data analysis: Collect, clean, and analyze large datasets to identify patterns and trends
* Modeling: Develop predictive models and algorithms to solve complex business problems, whose solutions could stem from a variety of ML fields
* Communication: Communicate findings and insights to stakeholders in a clear and concise manner, gather requirements on further adoptions and future work.
* Converting data into insights
Requirements:
* Minimum 2 years hands-on industry experience with ML, AI, MLOps or data science projects.
* Master’s degree in a quantitative field (e.g.computer science, mathematics, physics, engineering, bioinformatics);
* Expert and up-to-date knowledge of supervised and unsupervised machine learning techniques.
* Fluent in Python and in using common machine learning libraries (e.g., sklearn, pytorch/keras/tensorflow/opencv, etc.).
* Familiar with MLOps frameworks, machine learning model deployment formats as well as cloud based ML pipelines.
* Familiar with agile software development and knowledge of professional software development practices, tools for source control and project management especially Git and Azure DevOps.
Responsibilites:
* Data analysis: Collect, clean, and analyze large datasets to identify patterns and trends
* Modeling: Develop predictive models and algorithms to solve complex business problems, whose solutions could stem from a variety of ML fields
* Communication: Communicate findings and insights to stakeholders in a clear and concise manner, gather requirements on further adoptions and future work.
* Converting data into insights