Director, Cheminformatics - Modeling & Informatics

MSD•Boston, MA

3d•$236,000 - $371,500•Onsite

About The Position

The Director, Cheminformatics – Modeling & Informatics will lead cheminformatics and data science innovation to amplify pipeline impact across the discovery organization. The role sets direction for capabilities that support scientific decision-making throughout drug discovery and leads a multi-site team of cheminformatics professionals across data engineering, analytics, and scientific software development. The director will develop talent and foster a diverse, inclusive, high-performing team through sustained engagement with stakeholders in chemistry, biology, IT, and other functions. The team translates scientific questions into scalable data architectures, workflows, and algorithmic innovations that can be deployed across programs. The director will partner with research IT and project teams to embed cheminformatics solutions into the DMTA cycle, balance investment in new capabilities with use of existing solutions, and help shape data science strategy and a data-fluent culture across the organization. Modernization efforts may include machine learning, knowledge graphs, and emerging AI approaches. The position is based primarily in Boston, Massachusetts, with additional locations potentially available. The role includes 10% travel, domestic relocation, and visa sponsorship. Compensation for the primary location is $236,000–$371,500 in base salary, with eligibility for an annual bonus and long-term incentive, if applicable.

Requirements

PhD and 7 or more years of professional experience applying computational and data science approaches to interdisciplinary scientific problems in drug discovery; or MS and 9 or more years of experience; or BS and 13 or more years of experience.
At least 2 years of managerial experience, with demonstrated strength in team building, talent development, and inclusive leadership.
Experience designing and implementing modern computational workflows, including coding best practices, cloud-based systems, and MLOps/DataOps approaches.
Strong understanding of cheminformatics, data analytics, and data engineering in early drug discovery.
Experience enabling predictive modeling and advanced analytical approaches in a collaborative, matrixed environment.
Demonstrated ability to collaborate across functions and influence strategy across scientific and technical domains.
Experience engaging effectively with IT organizations to co-develop scalable platforms.
Strong communication and stakeholder engagement skills, including the ability to translate complex technical concepts into actionable solutions.
A degree in cheminformatics, bioinformatics, chemistry, biology, biochemistry, physics, statistics, computational chemistry, computational biology, data science, AI/ML, computer science, math, pharmaceutical sciences, engineering, or a related STEM field.

Responsibilities

Set the vision and strategy for cheminformatics capabilities and platforms that accelerate scientific learning and decision-making in drug discovery.
Lead a multi-site team of cheminformatics and data science specialists spanning data engineering, analytics, and scientific software development.
Develop talent, foster diversity of thought, and build an inclusive culture that engages and empowers team members.
Engage stakeholders across drug discovery, from early target identification and chemical biology through lead optimization and safety, to understand needs and enable impactful solutions.
Translate scientific challenges into scalable data architectures, workflows, and algorithmic approaches that can be leveraged across multiple projects.
Drive development of next-generation cheminformatics workflows using modern technologies, including machine learning, knowledge graphs, and emerging AI approaches.
Ensure capabilities are effectively deployed and adopted in collaboration with project teams and modeling partners.
Build and maintain partnerships with IT to co-develop robust, sustainable platforms for scientific workflows.
Balance strategic investment in new capabilities with effective use of existing solutions to maximize organizational value.
Collaborate with leaders in Bioinformatics, Biostatistics, Quantitative Biology, and Modeling to align data science strategy and priorities.
Contribute to cross-divisional alignment on the role of data science and informatics in the organization.
Work with Modeling, Structure, and Biophysics leadership to identify opportunities for cheminformatics to enhance modeling and discovery.
Maintain visibility across the discovery portfolio to identify emerging needs and opportunities for scalable cheminformatics support.