The Machine Learning Scientist/Sr Scientist, Federated Benchmarking & Validation Engineering plays an essential role within the TuneLab platform, responsible for identifying, assessing, and implementing cutting-edge algorithmic solutions that leverage diverse datasets while ensuring data privacy and security for our biotech partners
Job Summary
The Machine Learning Scientist/Sr Scientist, Federated Benchmarking & Validation Engineering plays an essential role within the TuneLab platform, responsible for identifying, assessing, and implementing cutting-edge algorithmic solutions that leverage diverse datasets while ensuring data privacy and security for our biotech partners.
This position will be instrumental in advancing both Lilly's pipeline and our partners' drug discovery efforts by designing critical algorithms and workflows that expedite the creation of transformative therapies.
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).
Matching Summary
The Machine Learning Scientist/Sr Scientist, Federated Benchmarking & Validation Engineering plays an essential role within the TuneLab platform, responsible for identifying, assessing, and implementing cutting-edge algorithmic solutions that leverage diverse datasets while ensuring data privacy and security for our biotech partners.
Salary
Base: $151,500 - $244,200; Bonus/Equity: Company bonus; Benefits: Comprehensive benefit program
Skills & Requirements
Must-have
Federated learning algorithms
Privacy-preserving test sets
Benchmark suite development
Model reproducibility infrastructure
Statistical validation rigor
Nice-to-have
Drug discovery expertise
AI/ML regulatory knowledge
GxP compliance experience
Portfolio mindset
Scientific rigor commitment
Key Requirements
PhD in Computational Biology, Bioinformatics, Cheminformatics, Computer Science, Statistics, or related field
2+ years of experience in biopharmaceutical industry