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