Senior Machine Learning Engineer - Real World Evidence
June 12
🏡 Remote – Anywhere in California
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
• 11 paid holidays • Generous Accrued Time Off increasing with years of service • Generous paid sick time • Annual day of service
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