Proven experience with data science and machine learning libraries in Python such as SciPy, NumPy, TensorFlow, and scikit-learn., Strong background in cloud development environments, especially Azure, Data Factory, PySpark, Scala, and DataBricks Delta., Experience in building data science models for user-facing applications, including recommendation systems., Knowledge of big data tools like Hadoop, Spark, Kafka, and databases such as Postgres and Cassandra..
Key responsibilities:
Develop and deploy data science and machine learning models for applications.
Work with cloud-based data processing and storage solutions, including Azure and DataBricks.
Implement data pipelines and workflows using tools like MLflow and AirFlow.
Collaborate on integrating models with front-end systems and ensure scalable deployment.
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