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Head Of Machine Learning - Real World Evidence - Europe

Remote: 
Full Remote
Contract: 
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

Bachelor's degree in computer science, data science, or related field; MS, PhD preferred, Minimum 8 years experience in machine learning or related field, with a focus on healthcare and RWE, Proven track record leading high-performing teams, deep understanding of ML algorithms, statistical modeling.

Key responsabilities:

  • Lead team to develop ML solutions for RWE analysis
  • Define and execute ML strategy within RWE domain, collaborate with teams to translate business needs into projects
  • Identify opportunities for innovation using ML, maintain data quality and security, stay updated on advancements in ML and RWE
  • Develop best practices for ML model development, deployment, and monitoring, communicate complex concepts to stakeholders
  • Manage relationships with partners, vendors, stakeholders to drive collaborative initiatives and stay informed on industry trends and regulations
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Luminary Group Startup https://luminarygroup.co.uk/
2 - 10 Employees
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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.

Required profile

Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Verbal Communication Skills
  • Analytical Thinking
  • Open Mindset
  • Leadership Development

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