Lilly is looking to advance its pipeline by designing critical algorithms and workflows that expedite the creation of transformative therapies. The Advisor Federated Learning Data Scientist will be instrumental in creating sophisticated models that can simultaneously learn to predict multiple, related endpoints from decentralized data sources, addressing the challenges of learning from heterogeneous clients.
Requirements
- PhD in a data science field such as Biostatistics, Statistics, Machine Learning, Computational Biology, Computational Chemistry, Physics, Applied mathematics, or related field from an accredited college or university
- Minimum of 2 years of experience in the biopharmaceutical industry or related fields, with demonstrated expertise in drug discovery and early development.
- Experience in developing statistical and machine learning models for complex endpoints.
- Broad understanding of emerging scientific and technical breakthroughs.
- Ability to quickly adapt to changing circumstances, learn from past experiences, and apply those learnings to new situations.
- Strong ability to think with a portfolio-level mentality, ensuring that individual program decisions align with the overall goals of Catalyze360.
- Independent, self-starter, work without supervision
Responsibilities
- Architect and implement advanced multi-task learning (MTL) models that effectively leverage shared representations across tasks to improve predictive performance and data efficiency in a federated ecosystem.
- Develop novel algorithms specifically designed to address extreme task and feature heterogeneity across clients.
- Investigate and apply techniques to manage the balance between shared and task-specific learning.
- Implement regularization methods to prevent negative transfer (where learning one task hurts the performance of another) and encourage positive knowledge sharing.
- Collaborate closely with domain experts and stakeholders to define complex biological or chemical endpoints.
- Translate these scientific problems into a well-posed multi-task learning framework, identifying relevant tasks and data sources.
- Establish rigorous validation and evaluation frameworks for federated multi-task models.
Other
- Plays an essential leadership role
- Exceptional interpersonal and communication skills, with a keen ability to understand, empathize, and navigate complex relationships and dynamics
- Outstanding EQ, problem-solving, analytical, project management skills.
- Highly self-motivated and organized.
- Demonstrated ability to connect and influence at various levels across disciplines, both externally and internally.
