Reimagine the infrastructure of cancer care within a community that values integrity, inspires growth, and is uniquely positioned to create a more modern, connected oncology ecosystem. Improve and extend lives by learning from the experience of every person with cancer.
Requirements
- You have 4+ years of hands on experience building predictive models for real world healthcare and drug development use cases
- You are proficient with advanced machine learning techniques including deep learning approaches (e.g. neural networks, variational autoencoders, generative adversarial networks) and causalML methods
- You have a strong knowledge of time to event analysis methods and other epidemiological methods commonly used in retrospective real world evidence generation
- You love working with data and have experience exploring it with a critical and thoughtful eye
- You are proficient in open source data science tools and language (R and Python)
- You have experience collaborating with researchers in the life science industry, academia, or government agencies to design and deliver high-quality studies that meet their needs
- You have oncology experience, particularly predicting cancer outcomes
Responsibilities
- Drive the design and development of innovative AI/ML solutions for pharma use cases impacting drug development and patient care
- Design and prototype advanced analytic and machine learning solutions leveraging multimodal real world data (RWD)
- Generate comprehensive reports detailing model training, performance and extracted insights, and effectively communicate findings and recommendations to the study teams and clients
- Lead preparations and authorship of abstracts, manuscripts and publications related to predictive modeling projects
- Work collaboratively with multidisciplinary teams such as project managers, clinicians and other stakeholders to design, execute and deliver on client-sponsored predictive modeling studies in an accurate, effective, and timely manner
- Advance the methodologies and applications of real-world data and AI/ML to shape the future of insights and evidence generation for the life sciences sector
Other
- You’re a kind, passionate and collaborative problem-solver.
- You are an analytical thinker and excellent communicator
- You hold a PhD degree in quantitative field such as machine learning, data science, statistics/biostatistics or applied mathematics with 3 - 4 years of relevant experience (can include work experience before graduate school) or a Master’s degree in one of these fields with 6 - 8 years of relevant experience
- You have strong organizational, time-management, prioritization and decision-making skills necessary to evaluate, plan and implement multiple high-visibility projects in a timely fashion
- You know how to balance attention to detail with execution against tight timelines
