Head Of Machine Learning - Real World Evidence - United States

Job Description

Job Description

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.

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