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Senior Machine Learning Engineer - RWE - Europe

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

Bachelor's degree in computer science, data science, or related field; advanced degree preferred, Minimum 4 years experience in machine learning engineering or data science, healthcare and RWE focus, Strong knowledge of machine learning algorithms, statistical modeling, and data mining techniques, Proficiency in Python or R for data preprocessing, analysis, and model implementation, Experience with TensorFlow, PyTorch, or scikit-learn.

Key responsabilities:

  • Design, develop, and deploy ML models to analyze RWE datasets
  • Collaborate with teams to understand business requirements and provide technical solutions
  • Preprocess and clean large-scale RWE data for quality and integrity
  • Evaluate and select ML techniques, tools, frameworks for specific use cases
  • Optimize ML models for scalability, performance, and accuracy
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Luminary Group Startup https://luminarygroup.co.uk/
2 - 10 Employees
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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:
  • Design, develop, and deploy machine learning models and algorithms to analyze complex RWE datasets.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Preprocess and clean large-scale RWE data to ensure quality and integrity.
  • Evaluate and select appropriate machine learning techniques, tools, and frameworks for specific use cases.
  • Train, fine-tune, and validate machine learning models using state-of-the-art methodologies and techniques.
  • Optimize machine learning models for scalability, performance, and accuracy.
  • Monitor and maintain deployed machine learning models, ensuring their ongoing performance and relevance.
  • Stay up-to-date with the latest trends and advancements in machine learning and real-world evidence.
  • Communicate findings and insights to both technical and non-technical stakeholders.

Requirements

  • Bachelor's degree in computer science, data science, or a related field; advanced degree preferred.
  • Minimum of 4 years of experience in machine learning engineering or data science, with a focus on healthcare and real-world evidence (RWE).
  • Strong knowledge of machine learning algorithms, statistical modeling, and data mining techniques.
  • Proficiency in programming languages such as Python or R for data preprocessing, analysis, and model implementation.
  • Experience with machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn.
  • Solid understanding of database systems and SQL for data manipulation and querying.
  • Experience with big data technologies and distributed computing frameworks is a plus.
  • Strong problem-solving and analytical skills, with the ability to find creative solutions to complex problems.
  • Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
  • Experience in the healthcare industry and familiarity with healthcare data standards is preferred.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Problem Solving
  • Communication
  • Collaboration

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