Sr. Manager, Scientific Computing
Cambridge, MA, United States
We are seeking an experienced and dynamic Senior Manager of Scientific Computing to lead our global scientific computing initiatives. This role will focus on supporting and enhancing our capabilities in machine learning operations (MLOps), scientific computing, bioinformatics computing, and pipeline management. The ideal candidate will have a strong background in computational science, experience in managing high-performing teams, and a passion for advancing scientific research through technology.
Key Responsibilities:
Leadership and Strategy: Lead a team of scientific computing professionals. Develop and implement strategies to support the computational needs of global research initiatives.
MLOps Support: Oversee the development and maintenance of machine learning models, ensuring robust, scalable, and efficient operations.
Scientific Computing: Manage and enhance computational resources and services for diverse scientific research projects.
Bioinformatics Computing: Provide specialized support for bioinformatics computing, including data analysis, visualization, and interpretation.
Pipeline Management: Develop and maintain efficient data processing pipelines to support large-scale scientific research.
Collaboration: Work closely with researchers, IT staff, and external partners to ensure the alignment of scientific computing resources with research objectives.
Innovation: Keep abreast of emerging technologies and trends in scientific computing and MLOps, and integrate innovative solutions into our operations.
Global Support: Ensure the availability, reliability, and scalability of computing resources for a global user base.
Budget Management: Manage the budget for scientific computing resources and infrastructure.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Bioinformatics, or a related field. PhD is a plus.
At least 5 years of experience in scientific computing, with a focus on MLOps and bioinformatics.
Experience in managing and leading technical teams.
Strong knowledge of data processing pipelines, cloud computing, and big data technologies.
Experience with machine learning tools and frameworks.
Excellent problem-solving and project management skills.
Strong communication and interpersonal skills.
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