Executive Director, Computational Biology - Oncology

Roche•South San Francisco, CA

61d•Onsite

About The Position

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide. This role will ensure that gRED and pRED are supported and enabled with world-leading data, analytical, and computational biology approaches in Oncology while developing our projects through the pre-clinical and clinical stages. This role is a leader of leaders, leading teams with a broad scope of bioinformatics, biostatistics, specialised disease and data science expertise with a primary focus on Oncology. As the Executive Director of Computational Biology - Oncology, you lead a team developing innovative data analysis solutions for target identification, target assessment, disease understanding, molecule characterization (mode of action, safety, etc.), improving predictive validity of pre-clinical models as well as supporting clinical development strategies by characterizing patient populations and identifying biomarker candidates. You drive impact on the gRED and pRED portfolio, build strong stakeholder relationships, and set strategy for your team and Roche. Your responsibilities include making decisions on talent, resourcing, business processes, and capability development, contributing to the organization's overall success.

Requirements

PhD in a scientific or technical field with 15+ years of experience, including significant group management and team formation
Deep expertise in computational biology, bioinformatics, biostatistics, data science, or similar fields
Proven expertise in pre-clinical and clinical research in Oncology.
Proven experience leading large teams, involving multiple stakeholders, and achieving outstanding results efficiently
Excellent partnering and collaboration skills, building trustful partnerships with internal and external stakeholders
Deep understanding of how biological data analysis impacts decision-making along the value chain
Ability to lead a multidisciplinary team, quickly understand topics, formulate problem statements, and achieve successful outcomes
Willingness to travel regularly to ensure exchange with your global team members and stakeholders.
Thrives in ambiguity, identifying opportunities, and bringing clarity to the team while fostering a growth mindset and development opportunities for direct reports.

Responsibilities

Strategic leadership of the Computational Biology - Oncology department within Computational Center of Excellence and member of the Computational Biology and Medicine LT
Define vision and strategy for computational biology in Oncology to achieve gRED and pRED objectives and implement world-leading approaches in portfolio projects to identify and assess new targets and to support the characterization of molecules and models that inform data driven decisions along the value chain.
Responsible for hiring, developing, and retaining talent, fostering an environment for team members to broaden their skills for enhanced outcomes
Ensure standardized tools and pipelines for computational biology, collaborating closely with biologists and computational leaders for efficient data flow and decision-making
Drive innovation in analysis approaches, establish strong internal and external partnerships, and lead by example to demonstrate and align with our core values

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