Measuring, monitoring, optimizing and recommending changes to productionized models.
Managing infrastructure associated with machine learning and advanced analytics.
Transforming and converting data science prototypes.
Performing statistical analysis.
Running machine learning tests including existing deployment improvements and new deployments, and ensuring the broader team understands the limitations of each model.
Identifying differences in data distribution that influences model performance.
Working closely with the Principal ML Developer, Senior Data Scientist and Data Scientist to identify effective models to optimize various water treatment processes.
Requirements:
Bachelor’s Degree in computer science, Economics, Physics, Engineering or related discipline.
7 - 8 years of experienced in delivering machine learning for practical applications.
Practical experience with ML algorithms, techniques and packages.
Demonstrated capability in a developer role, ideally with analytical experience.
Experience with the data science ecosystem including Python.
Hands on experience with Kubernetes.
Experience in building and running Docker images.
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