Head – Machine Learning and Computational Sciences

Head – Machine Learning and Computational Sciences

Requirements

• PhD or advanced degree in Computational Chemistry, Computational Biology, Engineering, Mathematics, Physics, Chemistry, Computer Science or Life Sciences with 15+ years’ experience in biotechnology/ biopharmaceutical industry.
• Excellent leadership qualities, strategic thinking, communication & presentation skills, broad expertise in computational research and strong experience with scientific programming, IT systems and platforms.
• Ability to clearly cut through complexity to define a clear portfolio based strategy that key stakeholders can align behind.
• Effective and crisp communication in a variety of formal presentation settings: one-on-one, small and large groups, with peers, direct reports and Pfizer senior management.
• Good at figuring out work processes necessary to get things done; knows how to organize people and activities; understands how to separate and combine tasks into efficient workflow.
• Knowledgeable about how organizations work; knows how to get things done both through formal channels and the informal network.
• Can effectively cope with change; can shift gears comfortably; can decide and act without having the total picture.
• Uses his/her time effectively and efficiently; values time; concentrates his/her efforts on the more important priorities; gets more done in less time than others; can attend to a broader range of activities.
• Move work forward with urgency and courage and address difficult conversations in a transparent and effective manner.
• Relevant and substantial technical experience in some or all of the following areas: Computational Chemistry / Cheminformatics, Computational Biology / Bioinformatics, Molecular/Cell Biology, Biochemistry, and Genetics, Macromolecular modeling and biophysics, Applied Mathematics, Statistics and/or Machine Learning, Scientific Programming and/or Computing, Biomedical engineering.

Responsibilities

• Establishing and maintaining an industry leading organization ensuring that all the requisite scientific and technical resources, talent, work processes, and systems are in place for designing and delivering new computational models and algorithms.
• Serving as the single point of accountability for scientific, strategic and operational initiatives pertaining to the MLCS organization and its projects, and establishing and maintaining strong technical and collaborative interactions with groups within P&TS, the Digital Organization, and numerous external partners.
• Responsible for scientific computing software and infrastructure on High Performance Computing (HPC) systems and Amazon Cloud platforms supporting above functions.
• Deliver cheminformatics and data engineering expertise and software engineering to support strategic initiatives in Med Design.
• Chair ML Stakeholder Group meeting in Medicine Design, comprising disciplines of med chem design and synthesis, structural biology, and computational chemistry. Define strategic portfolio of ML models, tools, and capabilities that align with portfolio project needs, external collaborations, pre-competitive frameworks, and a sustainable suite of software applications for end-users.
• Member of the Integrative Biology LT, aligning stakeholder needs in the TAs with MLCS expertise and project portfolio for target selection, omics infrastructure and pipeline development, partnering with Pfizer Digital. Responsible for R&D data and software engineering team for omics data and analysis ecosystem.
• Partner with the Digital organization and subject matter experts throughout P&TS to ensure that the best computational innovations are implemented in such a way to maximize access and adoption, while adopting appropriate technical standards for sustainability and re-use.
• Actively survey the external environment for cutting-edge computational methods with applicability towards drug discovery and development.
• Member of enterprise AI Council Pillar teams (e.g. Value and Execution, Strategy) and new R&D AI Portfolio Strategy Team.

Preferred Qualifications

• Ability to collaborate with internal and external stakeholders in a professional and enthusiastic manner.
• Ability to work well on multiple tasks and effectively prioritize to meet personal and team goals in a matrixed team environment.