Senior Scientist, Drug Discovery Biology; Target Biology & MoA

Senior Scientist II

Biomedical Research (BR) is the innovation engine of Novartis, focused on advancing transformative technologies to deliver therapeutic breakthroughs for patients. We are seeking a Senior Scientist to bring deep molecular target biology expertise and rigorous, hypothesis-driven experimentation to support mechanism of action (MoA) deconvolution and target validation in multiple diseases areas. This role combines hands-on experimental biology with strong data literacy, leveraging databases, digital tools, and AI-enabled approaches to refine hypotheses, guide experimental design, and accelerate decision-making.

You will operate at the interface of biology and data, contributing to high-impact drug discovery programs.

Position Location:

Cambridge, MA, onsite

The Drug Discovery Biology group in Cambridge is seeking a highly motivated Senior Scientist to advance the discovery of novel therapeutics and targets. As part of the global Discovery Sciences department, you will collaborate across disease areas and disciplines, contributing to diverse projects with measurable impact on drug discovery programs. This role offers a unique opportunity to combine deep biology expertise with data-driven approaches in a highly collaborative and innovative environment.

Key Responsibilities:

• Independently plan and execute hypothesis-driven experiments (with guidance from project leadership) to establish mechanistic clarity for targets and pathways.
• Design and run functional biology assays relevant to membrane proteins such as GPCRs, ion channels (e.g., signaling, trafficking, functional readouts), selecting the right model and readout for the mechanistic question.
• Build MoA packages by integrating genetic/pharmacologic approaches, phenotypic, and pathway data; propose follow-up experiments that close key uncertainties and reduce risk in target validation decisions.
• Apply digital tools, data analysis, and institutional knowledge to interpret results and refine experimental design. Demonstrate literacy in navigating databases (e.g., genetics/omics/protein resources, internal knowledge bases where applicable) to translate evidence into testable hypotheses and prioritize experiments.
• Use AI tools appropriately to improve literature synthesis, hypothesis generation, experiment planning, and analysis workflows; demonstrate foundational AI fluency and responsible use aligned with enterprise expectations. Collaborate effectively with computational partners (data science) to connect model outputs with experimentally testable biology.
• Contribute intellectually to project success through problem solving, proposing experimental options, and communicating recommendations clearly in team settings.
• Work fluidly across disease areas and across disciplines, maintaining effectiveness independent of reporting lines when needed.
• Support and mentor junior colleagues/students through coaching on experimental design, execution, and scientific thinking.
• Maintain high-quality documentation in ELN, ensuring reproducibility, compliance, and adherence to safety standards.

Essential Requirements:

• Recent PhD (within last 2 years) in Cell Biology, Molecular Biology, Pharmacology, Biochemistry, Chemical Biology, Systems Biology, Bioengineering, or related discipline.
• Depth in membrane protein biology experience (GPCRs and/or ion channels).
• Demonstrated hands-on experimental strength in molecular/cell biology (e.g., interrogation of functional readouts).
• Evidence of strong hypothesis-driven thinking, experimental troubleshooting, and the ability to translate complex biology into clear next experiments.
• Data literacy: comfortable using databases and multiple data sources to support research activities and experimental decisions.
• Clear written and oral communication skills in English; can communicate results to cross-functional teams.

Desirable Requirements:

• Prior exposure to human disease relevant biology, or strong motivation to build depth quickly; interest in remaining cross-disease-area adaptable.
• Experience with multi-modal evidence integration (e.g., genetics + omics + functional assays) for target validation and MoA.

Compensation and Benefits:

T…