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Core Responsibilities
Forecasting Excellence: Develop and implement advanced forecasting methodologies using technologies like batch forecasting, deep learning, simulation, and reinforcement learning to enhance decision-making.
Collaboration: Partner with leaders in various departments to identify business needs and deliver fit-for-purpose forecasts that drive tangible business value
Technical Implementation : Establish forecasting standards, tools, and practices, ensuring best practices in model development, including cross-validation and hyperparameter tuning.
MLOps / Engineering: Work with MLOps to streamline model deployment, monitoring, and maintenance. Implement CI/CD practices for robust forecasting solutions and optimize machine learning models.
Business Outcomes: Align forecasting efforts with strategic objectives to identify risks and opportunities, driving actionable decision-making.
System Integration: Integrate forecasting models with other business systems for a comprehensive view of performance, ensuring smooth data flow and interoperability.
Thought Leadership: Stay updated with advancements in forecasting and AI, identify new opportunities for data science solutions, and influence executive leaders in the strategic use of ML, AI, GenAI, and advanced analytics.
Experience Requirements
PhD in Statistics, Economics, Computer Science, Engineering or a STEM related field with a focus on forecasting and decision optimization.
Hands-on experience in developing and deploying forecasting and optimization models.
In-depth knowledge of forecasting methodologies, including, time-series forecasting, probabilistic simulation, financial modeling, and optimization
Proficiency in the latest Python, AWS, Azure, and open-source data science tools .such as R, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, and Scikit-learn.
Ability to work with large-scale datasets and perform efficient data analysis.
Ability to continuously track, evaluate, adapt the latest advancements in deep learning techniques and AI/ML research to business use cases across GE HealthCare.
Strong problem-solving skills and the ability to think critically and creatively.
Ability to communicate complex forecasting and technical ideas to non-technical stakeholders, including senior leaders.
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