Scientific Director, Cheminformatics AI/ML

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 the 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