Description

You will bridge the gap between data science and engineering to deploy and scale machine learning models in production.

Responsibilities

• Operationalize complex machine learning models through end-to-end deployment.
• Design, develop, and maintain adaptable data pipelines for specific use cases.
• Integrate ML use cases into business pipelines by collaborating with upstream and downstream teams.
• Develop and maintain pipelines to generate and publish model performance metrics for model review cadences.
• Support operationalized models and create maintenance runbooks.

Required Skills

• 10+ years of professional experience.
• Deep understanding of standard Machine Learning algorithms including Regression and Classification.
• Experience with Natural Language Processing concepts such as sentiment generation, topic modeling, and TFIDF.
• Working knowledge of scikit-learn, vader sentiment, pandas, and PySpark.
• Proficiency in Data Science workflows and model scaling.
• Ability to collaborate with data science and engineering teams to deploy algorithms.

Key Skills

Education

Any Gradute