Responsibilities

• Design, develop, and deploy production-grade machine learning models.
• Build predictive, forecasting, and probabilistic models for business use cases.
• Perform feature engineering, data preparation, and model validation; monitor model performance to ensure reproducibility and reliability.
• Integrate ML solutions with enterprise data platforms and BI applications.
• Implement MLOps practices, automated testing, and deployment pipelines.
• Collaborate with cross-functional teams to deliver AI-driven business solutions.

Requirements

Nice to have:

• Strong Python programming skills for ML development.
• Experience deploying machine learning models into production environments.
• Experience with forecasting, predictive analytics, or probabilistic modeling.
• Knowledge of feature engineering, model validation, and performance monitoring.
• Experience with MLOps practices and automated deployment.
• Understanding of explainable and responsible AI principles.
• Experience integrating ML solutions with enterprise data platforms.
• Experience with Monte Carlo simulations or other stochastic methods.
• Experience with Azure Machine L

Responsibilities

• Design, develop, and deploy production-grade machine learning models.
• Build predictive, forecasting, and probabilistic models for business use cases.
• Perform feature engineering, data preparation, and model validation; monitor model performance to ensure reproducibility and reliability.
• Integrate ML solutions with enterprise data platforms and BI applications.
• Implement MLOps practices, automated testing, and deployment pipelines.
• Collaborate with cross-functional teams to deliver AI-driven business solutions.

Requirements

Nice to have:

• Strong Python programming skills for ML development.
• Experience deploying machine learning models into production environments.
• Experience with forecasting, predictive analytics, or probabilistic modeling.
• Knowledge of feature engineering, model validation, and performance monitoring.
• Experience with MLOps practices and automated deployment.
• Understanding of explainable and responsible AI principles.
• Experience integrating ML solutions with enterprise data platforms.
• Experience with Monte Carlo simulations or other stochastic methods.
• Experience with Azure Machine L

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Legal

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• Terms
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