Scientific Director, Cheminformatics AI/ML

1 month ago

Boston, United States MSD Full time

Job Description

We are seeking an experienced and skilled Cheminformatician and AIML data scientist to join the Cheminformatics group within Modeling and Informatics (M&I) at our Boston/Cambridge, MA or Rahway, NJ sites. This role requires exceptional interpersonal and problem-solving skills, as well as the ability to translate scientific needs into actionable plans for implementing data workflows and infrastructure that accelerate the decision-making process from hit identification to clinical candidate delivery across different therapeutic areas and modalities at our company.

M&I is a diverse and inclusive team within our Research Laboratories Discovery Chemistry organization, comprising approximately 60 computational chemists, cheminformaticians, and data scientists. We leverage cutting-edge capabilities in structure-based modeling, predictive science, and AI/ML to drive drug design and development globally, with a proven track record of pipeline impact. The selected candidate will work closely with the M&I team and world-class chemistry teams on innovative science that has a wealth of opportunities to impact drug discovery and ultimately save and improve patient lives.

Key responsibilities will include:

Scientific Innovation:

  • Lead the development and implementation of effective AI/ML and cheminformatics workflows to impact all aspects of the Design, Make, Test, and Analyze (DMTA) cycles, including compound idea generation, library design, synthesis planning, and data analysis.

  • Drive and deliver optimized informatics algorithms and workflows to expedite drug discovery pipelines for a broad portfolio of modalities, such as peptides, antibody-drug conjugates, and targeted protein degraders.

  • Initiate and apply novel ML, statistics, and cheminformatics techniques to improve hit identification and hit-to-lead processes for different screening technologies (mRNA display, DNA-Encoded Libraries, high-throughput screening, virtual screening).

  • Identify opportunities, and collaborate with research scientists, IT specialists, and data scientists to find creative cheminformatics solutions to data, workflow, infrastructure, analysis, and modeling challenges.

  • Effectively communicate scientific results internally and externally through presentations and publications.

  • Provide scientific mentoring and training to maximize team impact on pipeline and capability deliverables.

Leadership and management:

  • Manage 1~2 cheminformaticians and data scientists, fostering talent growth and career development for all direct reports.

  • Foster cross-functional collaborations with stakeholders in discovery chemistry, pharmacokinetics & pharmacodynamics, quantitative biosciences, therapeutic area biology, and information technology.

  • Identify and evaluate new cheminformatics and AI/ML technology and software from commercial sources, open innovation, or external collaborations, strategically incorporating vendor solutions to enable efficient data-driven drug discovery.

  • Promote a data-fluent culture that emphasizes the value of FAIR data and robust, generalizable computational pipelines.

  • Lead aspects of capability builds and working groups while participating in cross-functional matrix teams to advance computational drug discovery at our company.

Position Qualifications:

Education Minimum Requirement:

Ph.D. in cheminformatics, computational chemistry, chemistry, chemical engineering, or related fields.

Required Experience and Skills:

  • 7+ years of experience applying cheminformatics and AI/ML approaches to problem-solving in drug discovery, including data mining, method implementation, and workflow automation.

  • Comprehensive knowledge of drug discovery and medicinal chemistry, with the ability to effectively communicate with collaborative scientists from diverse backgrounds.

  • Broad understanding of modern data science methods, particularly machine learning, in advancing drug discovery (e.g., predictive modeling, generative modeling, retrosynthesis prediction, active learning, explainable ML).

  • Excellent oral and written communication skills, with the ability to positively influence team decisions.

  • Strong problem-solving skills with meticulous attention to detail.

  • Proficiency in scripting (Python and/or R), SQL, and cheminformatics toolkits (OEChem, RDKit, DeepChem) with practical application of these skills.

  • Expertise in machine learning libraries (TensorFlow, Keras, PyTorch, Pandas, Scikit-Learn).

  • Familiarity with workflow applications and data analytics software (Pipeline Pilot, Knime, Spotfire).

Preferred Experience and Skills:

  • Expertise in data analysis and modeling in fields such as high-throughput experimentation, DNA-encoded libraries, mRNA display screening, virtual screening, screening hit identification, lead optimization, modality drug design.

  • Experience with IT infrastructure such as database systems, cloud computing (such as Databricks, AWS), and high-performance computing in Linux environments.

  • Experience leading scientific initiatives or capability builds in a matrixed environment relevant to drug discovery.

  • Leadership and people management experience.

  • Track record of scientific publications in peer-reviewed journals.

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