Luminary Group
Head Of Machine Learning – RWE – United States
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.