Principal Scientist (Computational Chemistry)

SUMMARY: We are seeking a Principal Scientist in Computational Chemistry to join our small molecule discovery organization. The successful candidate will bring deep expertise in ligand design and cheminformatics with experience in a pharmaceutical or biotechnology drug discovery setting. Strong communication and collaboration skills are essential, as this position will interact closely with interdisciplinary small molecule discovery project teams. This individual will apply computational and data-driven methods to advance small-molecule discovery projects, collaborating closely with medicinal chemistry, structural biology, pharmacology and biology teams to advance early-stage discovery projects.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Apply and develop cheminformatics and machine learning models to enable predictive analytics across the pipeline

• Lead and contribute to ligand- and structure-based design efforts in active discovery programs

• Integrate computational & machine learning tools into collaborative platforms (e.g., LiveDesign, Spotfire) to make predictive insights accessible to cross-functional teams

• Experience in applying machine learning approaches, including protein-ligand/protein-protein co-folding models and generative chemistry models

• Analyze large data sets and apply cheminformatics techniques to extract design-relevant insights

• Drive virtual screening campaigns (structure-based, ligand-based, and fragment-based) to support hit identification and lead optimization

• Communicate results and strategy effectively to project teams and leadership

• Contribute to the strategic growth of CADD capabilities and help establish a predict-first culture within the organization

• Maintain notebooks in accordance with company policies and practices

EDUCATION & EXPERIENCE:

• Bachelor's degree in related discipline and a minimum of 11 years of relevant experience; or,

• Master's degree in related discipline and a minimum of 9 years of relevant experience; or,

• PhD in Computational Chemistry, Cheminformatics or related discipline and a minimum of 5 years of post-doctorate experience; or,

• Equivalent combination of education and experience.

KNOWLEDGE & SKILLS:

• Demonstrated impact on drug discovery projects, from hit ID through lead optimization

• Experience in cheminformatics, data analysis, and machine learning co-folding approaches

• Proficiency with Python/R, RDKit, Pipeline Pilot and ML frameworks

• Proactive mindset to bring open-source/external ML solutions in-house to enable design and decision-making

• Strong expertise in ligand- and structure-based drug design methods, including docking, scaffold hopping, virtual library enumeration, molecular dynamics, and free energy approaches

• Solid understanding of drug-like property optimization (ADME, physicochemical parameters, liabilities)

• Proven track record of effective collaboration with medicinal chemists, biologists, and other stakeholders.

• Strong communication and presentation skills; ability to influence project strategy with computational insights.

ADDITIONAL SKILLS & ABILITIES:

• Strategic thinker with a passion for applying computational & ML approaches to solve practical problems in drug discovery

• Collaborative team player, able to work seamlessly across disciplines

• Proactive, innovative, and adaptable in a fast-paced environment

• Strong balance of technical depth and project impact orientation

• Strong written, oral, and presentation communication skills

The preceding job description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.

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