Generative AI Associate Principal Scientist
Accountabilities:
- Collaborate with scientists from across the company to understand their challenges and work with them to build the platform that underpins their research.
- Take responsibility for designing, and deploying machine learning models for a large-scale analysis of clinical transcriptomics, proteomics, and cell painting data
- Design and build machine learning models for transcriptomics, proteomics and cell painting data to predict the risk of clinical events, patient segmentation, or for high-throughput compound screening
- Apply a range of data science methodologies, developing novel data science solutions where off-the-shelf methodologies do not fit
- Lead the development, and implementation of machine vision models in cell painting and advanced cell models space: from project ideation, through PoC to deployment in production in collaboration with colleagues from R&D IT
- Build and manage effective relationships with stakeholders to ensure utilization and value of information resources and services. Clearly and objectively communicate results, as well as their associated uncertainties and limitations to shape solutions
- Work effectively across several timezones with AI research teams in China, India, Europe and the US East Coast, communicating the requirements for the AI models and evaluating the available solutions
- Champion a “production first attitude” to ensure the necessary infrastructure and platforms are available to scale exploratory research to production.
- Be a part of a hard-working team, continuously improving Machine Learning development environments, platforms, and tooling.
- Work closely and collaboratively with internal governance and compliance functions such as Cyber Security and Data Privacy to secure the computing environment without obstructing end-user productivity.
