Senior Expert Data Science (Applied AI, LMW Drug Discovery)
Novartis
June 26, 2026
Remote friendly (Cambridge, MA)
United States
Clinical Research and Development
Key Responsibilities:
- Provide technical leadership for Applied AI initiatives in low molecular weight drug discovery
- Design and develop advanced machine learning models for molecular design and optimization
- Evaluate and benchmark state-of-the-art AI methods for drug discovery applications
- Drive innovation by identifying and implementing novel methodologies with measurable scientific impact
- Collaborate with cross-functional teams to integrate AI solutions into research workflows
- Ensure robustness, performance, and scalability of AI models through rigorous validation practices
- Translate model outputs into actionable insights for experimental and scientific decision-making
- Lead development of automated, agent-based workflows for computer-aided drug design pipelines
- Partner with engineering and product teams to deploy AI solutions into production
- Communicate progress, insights, and impact to senior stakeholders and scientific leadership
Essential Requirements:
- Deep curiosity and passion for biomedical science and therapeutic discovery
- At least 4 years of experience developing and deploying machine learning models and data solutions
- Strong programming expertise in Python and deep learning frameworks, with experience using version control systems
- Demonstrated expertise in generative chemistry, structure-based drug design, and molecular modeling techniques
- Experience applying artificial intelligence to molecular design, optimization, and drug discovery workflows
- Proven ability to collaborate across scientific domains within complex research organizations
Compensation and Benefits (as stated):
- Expected salary range: 138,600.00–257,400.00 USD annual; performance-based cash incentive; potential annual equity awards; US-based comprehensive benefits and time-off package.
- Provide technical leadership for Applied AI initiatives in low molecular weight drug discovery
- Design and develop advanced machine learning models for molecular design and optimization
- Evaluate and benchmark state-of-the-art AI methods for drug discovery applications
- Drive innovation by identifying and implementing novel methodologies with measurable scientific impact
- Collaborate with cross-functional teams to integrate AI solutions into research workflows
- Ensure robustness, performance, and scalability of AI models through rigorous validation practices
- Translate model outputs into actionable insights for experimental and scientific decision-making
- Lead development of automated, agent-based workflows for computer-aided drug design pipelines
- Partner with engineering and product teams to deploy AI solutions into production
- Communicate progress, insights, and impact to senior stakeholders and scientific leadership
Essential Requirements:
- Deep curiosity and passion for biomedical science and therapeutic discovery
- At least 4 years of experience developing and deploying machine learning models and data solutions
- Strong programming expertise in Python and deep learning frameworks, with experience using version control systems
- Demonstrated expertise in generative chemistry, structure-based drug design, and molecular modeling techniques
- Experience applying artificial intelligence to molecular design, optimization, and drug discovery workflows
- Proven ability to collaborate across scientific domains within complex research organizations
Compensation and Benefits (as stated):
- Expected salary range: 138,600.00–257,400.00 USD annual; performance-based cash incentive; potential annual equity awards; US-based comprehensive benefits and time-off package.