DataRobot Machine Learning Specialist

at  StratifyIQ

Overview The DataRobot ML Specialist is responsible for developing and optimizing machine learning workflows with a focus on forecasting, statistical analysis, and automation. This role involves working with structured and time-series data, leveraging AutoML and AutoTS platforms to improve model performance and scalability. Collaboration with data engineers, analysts, and business stakeholders is essential to ensure that machine learning solutions align with business objectives.

Required Qualifications

• Senior-level experience in machine learning, data science, or AI.
• Hands-on experience with DataRobot AutoML, AutoTS, or similar platforms (H2O.ai, Google AutoML, AWS SageMaker Autopilot, Azure AutoML).
• Strong understanding of forecasting techniques, statistical modeling, and ML concepts.
• Experience working with Azure cloud environments for machine learning applications.
• Ability to collaborate with cross-functional teams to implement ML-driven solutions

Preferred Qualifications

• Proficiency in Python, R, or SQL for data manipulation and ML model development.
• Experience in the energy industry, particularly with demand forecasting or grid analytics.
• Familiarity with MLOps, API integrations, cloud-based deployment strategies, and CI/CD pipelines.
• Background in automating data workflows and working with large-scale time-series data

• Design, develop, and optimize ML workflows within DataRobot AutoML, AutoTS, and similar platforms such as H2O.ai, Google AutoML, AWS SageMaker Autopilot, and Azure AutoML.
• Work with various types of structured and time-series data to develop predictive models.
• Implement and maintain MLOps best practices, ensuring models are deployed, monitored, and maintained effectively.
• Collaborate with data engineering and business teams to integrate machine learning models into production environments.
• Conduct exploratory data analysis, feature engineering, and model evaluation to improve accuracy and performance.
• Optimize forecasting models for data-driven decision-making in the energy sector.
• Leverage Azure-managed cloud environments for ML model deployment and workflow automation.

Required Qualifications

• Senior-level experience in machine learning, data science, or AI.
• Hands-on experience with DataRobot AutoML, AutoTS, or similar platforms (H2O.ai, Google AutoML, AWS SageMaker Autopilot, Azure AutoML).
• Strong understanding of forecasting techniques, statistical modeling, and ML concepts.
• Experience working with Azure cloud environments for machine learning applications.
• Ability to collaborate with cross-functional teams to implement ML-driven solutions.

Preferred Qualifications

• Proficiency in Python, R, or SQL for data manipulation and ML model development.
• Experience in the energy industry, particularly with demand forecasting or grid analytics.
• Familiarity with MLOps, API integrations, cloud-based deployment strategies, and CI/CD pipelines.
• Background in automating data workflows and working with large-scale time-series data.