Senior Machine Learning Engineer - RWE - United States

April 20

Luminary Group

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Description

• 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

Benefits

• Competitive compensation • Health insurance benefits • Retirement savings plan • Paid time off