Associate Director, Data Science, New Targets, Oncology

Role Summary

The Associate Director of Data Science will lead a multidisciplinary team focused on target discovery in oncology, using advanced analytics, new technologies, and close collaboration across the organization. The role demands strong scientific leadership, deep data science expertise in oncology, and innovative approaches to bring new drug targets to the pipeline.

Responsibilities

• Lead and develop a team of data scientists, driving high-quality data science grounded in biology to identify new targets for oncology drug development.
• Co-develop and execute a data science strategy to enable and enhance innovation in the new targets space.
• Align with the Target Biology and Discovery (TBaD) team and Oncology Drug Discovery Data Science teams to represent the New Targets data science function and manage the portfolio of New Targets projects.
• Collaborate on the development and implementation of machine learning algorithms, AI models, and platforms to deliver predictive and prescriptive insights.
• Contribute to the Oncology Data Science Leadership team and represent the New Targets portfolio as a function.
• Collaborate with Oncology Data Science engineering teams to adhere to data standards, governance, and strategy.
• Lead matrix teams focused on disease areas or technologies like genomics, proteomics, and spatial technologies.
• Present and externalize team work in conferences, abstracts, and scientific journals.

Qualifications

• This position is based at the Cambridge, MA site with 5% travel; remote work not available.
• Ph.D. in data science, computational biology, or related field with a strong oncology background; ability to set scientific strategy.
• 7+ years of data science experience in oncology drug development or relevant academic roles.
• 3+ years of direct people management experience with strong leadership skills.
• Understanding of oncology targets (mutated oncogenes) and identifying cell surface targets for modalities such as antibody-drug conjugates, CAR-T, and radioligand therapies.
• Broad experience with genomics, proteomics, and/or functional genomics data.
• Excellent communication skills for cross-functional teams and stakeholders.
• Proven contributions to the scientific community via papers or conference presentations.

Skills

• AI/machine learning expertise and statistical modeling techniques.
• Strong leadership and collaboration across diverse teams.
• Data governance and data standards proficiency.

Education

• Ph.D. in data science, computational biology, or related field with oncology focus.

Additional Requirements

• Onsite at Cambridge, MA; 5% travel required.