Machine Learning Engineer Predictive Modeler

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Machine Learning Engineer Predictive Modeler

Machine Learning Engineers and Predictive Modelers in health sciences are instrumental in harnessing the power of data and cutting-edge algorithms to revolutionize healthcare. Their role revolves around designing, developing, and deploying machine learning models and predictive analytics solutions to address healthcare challenges.

These professionals work in collaboration with healthcare researchers, data scientists, and clinicians to identify predictive variables, collect and preprocess healthcare data, and create robust models. They apply machine learning techniques to predict disease outcomes, optimize treatment plans, and improve patient care pathways

 

 

 

 

 

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Responsibilities

  • Develop predictive models for clinical and health outcomes.
  • Utilize machine learning algorithms to analyze complex datasets.
  • Collaborate with data scientists and researchers on model design.
  • Validate and refine models to ensure accuracy and reliability.
  • Implement models into clinical and pharmaceutical applications.
  • Stay updated with advancements in machine learning techniques.
  • Ensure compliance with health data standards and regulations.
  • Collaborate with IT teams for model deployment.
  • Continuously monitor and update models based on new data.
  • Provide insights and recommendations to stakeholders based on model predictions.
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Education

Educational prerequisites for Machine Learning Engineers and Predictive Modelers in health sciences typically include a bachelor's or master's degree in computer science, data science, biomedical informatics, or a related field. Proficiency in programming languages (e.g., Python), machine learning libraries (e.g., TensorFlow, scikit-learn), and domain knowledge in health sciences is essential.

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20+ Years Experience

20+ Years Experience

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Robust Talent Network

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Efficient Recruiting

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Focus On Compliance

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