Head Of Machine Learning – Real World Evidence – United States Full-time

Luminary Group is excited to announce a unique opportunity for an exceptional Head of Machine Learning with expertise in Real-World Evidence (RWE) to join our esteemed team. Reporting directly to the executive leadership, you will play a pivotal role in driving the strategy, innovation, and implementation of machine learning models and algorithms to derive meaningful insights from RWE data for the healthcare industry.
Responsibilities:

• Lead and inspire a team of talented machine learning engineers and data scientists to develop cutting-edge machine learning solutions for RWE analysis.
• Define and execute the machine learning strategy, roadmap, and vision within the RWE domain.
• Collaborate with cross-functional teams to understand business needs and translate them into actionable projects.
• Identify opportunities for utilizing machine learning to drive innovation and improve healthcare outcomes.
• Stay abreast of the latest advancements in machine learning and RWE, and lead the evaluation and adoption of emerging technologies.
• Ensure the quality, integrity, and security of RWE data used in machine learning models.
• Develop and maintain best practices and standards for machine learning model development, deployment, and monitoring.
• Communicate complex machine learning concepts and results to stakeholders in a clear and concise manner.
• Manage relationships with external partners, vendors, and key stakeholders to drive collaborative initiatives.
• Stay up-to-date with industry trends, regulations, and ethical considerations related to RWE and machine learning.

Requirements

• Bachelor’s degree in computer science, data science, or a related field; advanced degree (MS, PhD) strongly preferred.
• Minimum of 8 years of experience in machine learning, data science, or a related field, with a focus on healthcare and real-world evidence (RWE).
• Proven track record of leading and managing high-performing teams in machine learning or data science.
• Deep understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Expertise in programming languages such as Python or R, and proficiency in machine learning libraries and frameworks.
• Experience with big data technologies, distributed computing frameworks, and cloud platforms is preferred.
• Strong analytical and problem-solving skills, with the ability to develop innovative solutions to complex problems.
• Excellent communication and leadership skills, with the ability to influence and inspire teams and stakeholders.
• Experience in the healthcare industry and familiarity with healthcare data standards is highly desired.
• Publication record and active participation in relevant conferences or communities is a plus.