What are the responsibilities and job description for the Scientist I, Computational Biologist position at Metric Bio?
Metric Bio has partnered with a client focused on leveraging AI-driven computational biology to accelerate drug discovery and development. Our client is dedicated to transforming the pharmaceutical industry by integrating human-centric data and computational methods to enhance target discovery and prioritization across multiple therapeutic areas.
About the Role
We seek a computationally proficient biologist eager to apply their expertise to target discovery and prioritization efforts. As part of a cross-functional team comprising biologists and data scientists, the ideal candidate will utilize computational approaches to define and evaluate biological hypotheses, collaborating closely with data science experts and effectively communicating insights to a diverse scientific audience. This role bridges preclinical biology and translational data science, necessitating an interdisciplinary mindset and strong communication skills.
Responsibilities:
- Contribute to the identification and prioritization of novel therapeutic targets, particularly in cardiovascular disease and obesity, using computational methodologies.
- Define and prioritize biological research questions and relevant data sources for target discovery.
- Conduct feasibility assessments and exploratory analyses on internal and public datasets to support new research initiatives.
- Collaborate with data scientists to refine computational approaches and develop new methodologies.
- Interpret, summarize, and present biological insights to internal and external scientific audiences.
Qualifications:
- BS (10 years), MS (6 years), or PhD (2 years) in cell/molecular biology, computational biology, bioinformatics, biotechnology, or a related discipline.
- Expertise in cell/molecular biology, particularly in inflammation or metabolism, with preference for cardiovascular disease or obesity research.
- Proven ability to communicate complex biological questions and results effectively to diverse stakeholders through publications, presentations, or teaching.
- Proficiency in R and/or Python, including experience with version control.
- Strong ability to work independently and collaboratively in interdisciplinary settings.
- Excellent organizational skills and attention to detail.
- Exceptional cross-functional collaboration, communication, and interpersonal skills.
Preferred Qualifications:
- Experience analyzing and interpreting -omics data (genomics, transcriptomics, proteomics, metabolomics).
- Familiarity with cloud-based data platforms (e.g., AWS, Snowflake).
- Experience working with public datasets (e.g., GEO, LINCS) and real-world data sources (e.g., EHR, claims, disease registries).
This is an opportunity to contribute to a forward-thinking, data-driven approach to drug discovery. If you have the skills and passion to drive computational biology innovations, we encourage you to apply.
