Vertex Pharmaceuticals

Vertex Pharmaceuticals

Executive Director, Data & Methods (Data and Computational Sciences)

Boston, MA · Director

Sponsorship not specified$271k-$406kDetected 5 days ago
Machine LearningData EngineeringData ScienceRecruitingBioinformaticsResearchCommunication

About the role

  • The role will report to the Head of Data & Computational Sciences.
  • This is a Boston based, hybrid role (3 days/week onsite).
  • Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

Responsibilities

  • Lead a multidisciplinary organization of scientists, engineers, and managers - building structure, growing other leaders, and driving organizational effectiveness as a leader of leaders.
  • Build scalable platforms and scientific software - durable, production-grade, reusable capabilities that serve stakeholders across modalities, not one-off tools.
  • Partner with other technology leaders at Vertex to deploy research-grade methods into scalable platforms and define AI, compute, and data infrastructure needs
  • Attract, develop, and retain outstanding talent, fostering an inclusive, rigorous, high-trust culture - and translate complex science into clear recommendations for senior leadership.
  • Drive adoption and impact by ensuring computational methods, AI/ML tools, and data products are embedded in real scientific workflows and deliver measurable value to research teams.

Requirements

  • 15+ years of progressive experience in computational science, ML/AI, and scientific methods for drug discovery, with significant time in biotech, pharma, or comparably complex environments.
  • Deep, recognized expertise in at least one computational science domain (e.g. ML/AI for scientific applications, computational chemistry, computational biology), with credibility bridging multiple domains.
  • Strong scientific software engineering foundation and experience overseeing maturation of research-grade methods into production-grade systems.
  • Ability to balance scientific ambition with practical delivery, prioritizing capabilities that are robust, reusable, and aligned to research needs.
  • Advanced degree (PhD preferred) in Computational Chemistry, Computational Biology, Computer Science, Bioinformatics, Data Science, or a related field.

Compensation

  • $270,600 - $406,000
  • The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting.
  • This role is eligible for an annual bonus and annual equity awards.
  • Some roles may also be eligible for overtime pay, in accordance with federal and state requirements.
  • Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

Company info

  • The Flex status for this position is subject to Vertex's Policy on Flex @ Vertex Program and may be changed at any time.
  • Company Information
  • Vertex is a global biotechnology company that invests in scientific innovation.
  • Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law.
  • Vertex is an E-Verify Employer in the United States.
  • Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.
  • Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com

This listing is sourced directly from Vertex Pharmaceuticals's careers page and normalized into a canonical job model.