Senior Machine Learning Engineer - Real-World Evidence

Company: Luminary Group

Location: United States

Job Overview

Luminary Group is excited to partner with a world-leading life science company seeking a highly skilled and motivated Senior Machine Learning Engineer with expertise in Real-World Evidence (RWE). Join our team to develop and implement cutting-edge machine learning models and algorithms that analyze RWE data, delivering valuable healthcare industry insights.

Key Responsibilities

• Design, develop, and deploy machine learning models and algorithms for complex RWE datasets analysis.
• Collaborate with cross-functional teams to translate business requirements 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 to ensure ongoing performance and relevance.
• Stay updated with the latest trends and advancements in machine learning and real-world evidence.
• Communicate findings and insights to both technical and non-technical stakeholders.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, or a related field; advanced degree preferred.
• A minimum of 4 years of experience in machine learning engineering or data science, focusing 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.