About the Department
Computational Drug Design (CDD) is the Novo Nordisk organization where we develop and apply state of the art capabilities in data science, predictive modeling, and AI/ML to enable both ligand and structure-based drug design. Scientists within CDD collaborate seamlessly with teams across the globe to invent better molecules faster. With an unbiased approach to drug modalities, in-house access to the newest screening techniques, and world-class experimentation, we have a wealth of opportunities to impact our pipeline and save and improve patient lives. We work in multidisciplinary, highly collaborative discovery teams both locally and across Novo Nordisk's global network to invent novel medicines by applying advanced computational techniques and developing innovative computational methods. We engage in external collaborations to ensure access to innovative research and technology.
Small Molecule Digital Chemistry is dedicated to the research and development of small molecule therapeutics. Our role is two-fold: support cutting-edge pharmaceutical research projects and develop innovative computational technologies in digital chemistry field. To be successful, we foster strong collaborations with Small Molecule Medicinal Chemistry within our Global Research and Technology (GRT) organization and colleagues across the Data Science and Innovation (DSI) organization. Our mission is to deliver in silico models, cheminformatics tools and computational chemistry platforms to enable in silico small molecule drug design to benefit patients across the globe.
We believe in the value of a diverse and inclusive culture. Together, we build and grow talent to ensure the development of novel solutions. The team is comprised of collaborative, diverse and passionate people who have a true sense of pride in their work. We are committed to helping each other grow, and we are driven by the opportunity to make a difference in the lives of people living with chronic disease. Everything we do starts and ends with the patient. And, while changing the future of chronic disease treatment, such as diabetes and obesity, is no easy task, we also recognize the importance of an enjoyable workplace, which is why we have cultivated a culture of fun, ingenuity, and innovation. Our competitive compensation package and support of a healthy work-life balance all add to a best-in-class employee experience.
The Position
The Senior/Principal Data Scientist - Computational Absorption, Distribution, Metabolism, and Excretion (cADME) will contribute to the Small Molecule Digital Chemistry team's effort towards improved understanding of ADMET biological endpoints through research and development of in silico models. The Senior/Principal Data Scientist - cADME will have knowledge and experience in ADME data analysis and modeling, advanced computational modeling methods and small molecule project support. They will have working knowledge of common ADME data and tools and a high degree of proficiency in AI/ML predictive modeling using machine learning, cheminformatics, and HPC/cloud computing. They will be able to implement complex workflows to aggregate and prepare experimental data, generate predictive ML/AI models, execute virtual screening, and perform multi-objective optimization of small molecules. The Senior/Principal Data Scientist - cADME will champion an in-silico first mindset and show initiative in recognizing and addressing unmet scientific needs using internal and external data.
Relationships
This role reports to the Senior Scientific Director of SMDC. They will have close interactions with scientists and experts within Computational Drug Discovery, Medicinal Chemistry, Quantitative Biology and ADME & Tox. Additional internal partners include data scientists, data engineers, ML specialists, software developers and others across US, UK, and Denmark. External relationships include commercial and academic collaboration partners.
Essential Functions

• Advance Small Molecule pharmaceutical project portfolio through application of cADME modelling tools and DMPK principles.
• Research, implement and apply methods to identify the need and guide the design of in vitro and in vivo experiments.
• Lead research efforts to understand connectivity of in silico model predictions to in vitro and in vivo experimental ADMET data.
• Conceptualize approaches, identify capability gaps, and set goals within small molecule ADMET modeling and drug design
• Own the implementation and deployment of production quality computational ADMET models.
• Represent Small Molecule ADMET CDD on cross-functional research teams
• Prepare and present research in top-leading journals or conferences.
• Maintain a well-documented, reusable codebase, and traceable model history
• Maintain scientific and technical expertise through familiarity with scientific literature and attending conferences
• Work closely with Therapeutic areas, Research Chemistry and Computational Drug Discovery to drive discovery and development efforts
• Work with ML scientists and engineers to guide the development of our ML model infrastructure.
• Collaborate with colleagues from ADME, Tox, Computational Drug Discovery and ML to implement production quality global and local predictive models.
• Actively participate in virtual global team meetings regularly
• Participate in the evaluation of external and internal capabilities and facilitate collaborations with external partners
• Present results to interdisciplinary teams of experimental, modeling scientists and machine learning colleagues at company meetings.

Physical Requirements
Up to 10% overnight travel required.
Qualifications

• Ph.D. with 8+ years of relevant experience can be considered (or M.Sc. with 10+ years required). Degree in Cheminformatics, Computational Chemistry, Computational Biology or related quantitative field preferred
• Relevant experience includes:
  • Research experience in the field of small molecule drug discovery within industry or academia (industry preferred)
  • Solid understanding of DMPK principles
  • Proven track record of knowledge and use of ADMET modeling and cheminformatics methods and tools
  • Experience with QSAR/QSPR modeling, machine learning, and AI methods.
  • Experience in scripting or programming languages such as Python and workflowing methods.
  • Hands on experience with at least one major cheminformatics toolkit and artificial intelligence/machine learning platform (e.g. RDKit, PyTorch, Scikit-learn).
  • Ability to perform in-depth data analysis and develop algorithms to solve complex problems.
  • Excellent written and oral communication skills
  • Detail oriented with strong documentation skills
  • Familiarity with popular commercial in silico ADMET platforms
• Familiarity and working experience with a breadth of tasks of the Design-Make-Test-Analyze drug discovery cycle - highly preferred

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.
At Novo Nordisk we recognize that it is no longer good enough to aspire to be the best company in the world. We need to aspire to be the best company for the world and we know that this is only possible with talented employees with diverse perspectives, backgrounds and cultures. We are therefore committed to creating an inclusive culture that celebrates the diversity of our employees, the patients we serve and communities we operate in. Together, we're life changing.
Novo Nordisk is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, protected veteran status or any other characteristic protected by local, state or federal laws, rules or regulations.
If you are interested in applying to Novo Nordisk and need special assistance or an accommodation to apply, please call us at 1-855-411-5290. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.