
Data Science Professional
3 days ago
At VentureDive, we're seeking a talented Data Science Professional to join our team.
This role focuses on developing, deploying, and managing machine learning models to solve complex business challenges and create enterprise-grade applications. The ideal candidate will have a strong background in data science and machine learning, with proven hands-on experience in the end-to-end model lifecycle.
About the Role- We are looking for an expert who can design, develop, and implement machine learning models across various domains, including data preprocessing, feature engineering, model training, validation, and evaluation.
- The successful candidate will focus on building robust, scalable, and reliable machine learning applications that can be deployed and maintained in an enterprise environment.
- They will deploy and manage machine learning models in production environments, utilizing cloud platforms like Microsoft Azure (Azure Machine Learning, Databricks) or AWS (SageMaker, Glue).
- End-to-End Model Development: Design, develop, and implement machine learning models across various domains, including data preprocessing, feature engineering, model training, validation, and evaluation.
- Enterprise-Grade Applications: Focus on building robust, scalable, and reliable machine learning applications that can be deployed and maintained in an enterprise environment.
- Cloud Deployment & Management: Deploy and manage machine learning models in production environments, utilizing cloud platforms like Microsoft Azure (Azure Machine Learning, Databricks) or AWS (SageMaker, Glue).
- Master's degree in Data Science, Computer Science, Statistics, or a related field.
- Minimum of 4+ years of professional experience in developing, deploying, and managing machine learning models in production environments, with a focus on building scalable applications.
- Deep understanding of statistical concepts and machine learning algorithms, including their theoretical foundations and practical implementations.
- Proficiency in Python with proven hands-on experience using libraries such as pandas, scikit-learn, TensorFlow, or PyTorch.
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