Senior Machine Learning Engineer

Vor 2 Tagen

Zürich, Schweiz TN Switzerland Vollzeit

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Client:

Luminary Group

Location:

-

Job Reference:

bffb6e8775f3

Job Views:

9

Posted:

21.01.2025

Expiry Date:

07.03.2025

Job Description:

Luminary Group is currently in partnership with a world leading life science company who is currently seeking a highly skilled and motivated Senior Machine Learning Engineer with expertise in Real-World Evidence (RWE) to join their team. As a Senior Machine Learning Engineer, you will be responsible for developing and implementing cutting-edge machine learning models and algorithms to analyze RWE data and extract valuable insights for the healthcare industry.

Responsibilities:
  1. Design, develop, and deploy machine learning models and algorithms to analyze complex RWE datasets.
  2. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  3. Preprocess and clean large-scale RWE data to ensure quality and integrity.
  4. Evaluate and select appropriate machine learning techniques, tools, and frameworks for specific use cases.
  5. Train, fine-tune, and validate machine learning models using state-of-the-art methodologies and techniques.
  6. Optimize machine learning models for scalability, performance, and accuracy.
  7. Monitor and maintain deployed machine learning models, ensuring their ongoing performance and relevance.
  8. Stay up-to-date with the latest trends and advancements in machine learning and real-world evidence.
  9. Communicate findings and insights to both technical and non-technical stakeholders.
Requirements:
  1. Bachelor's degree in computer science, data science, or a related field; advanced degree preferred.
  2. Minimum of 4 years of experience in machine learning engineering or data science, with a focus on healthcare and real-world evidence (RWE).
  3. Strong knowledge of machine learning algorithms, statistical modeling, and data mining techniques.
  4. Proficiency in programming languages such as Python or R for data preprocessing, analysis, and model implementation.
  5. Experience with machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn.
  6. Solid understanding of database systems and SQL for data manipulation and querying.
  7. Experience with big data technologies and distributed computing frameworks is a plus.
  8. Strong problem-solving and analytical skills, with the ability to find creative solutions to complex problems.
  9. Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
  10. Experience in the healthcare industry and familiarity with healthcare data standards is preferred.
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