Digital Innovation Biologist / Biological Data Science

Role Description

 

As the leader in animal health, Zoetis is seeking a visionary and creative Senior or Principal Scientist to join its world-class Veterinary Medicine Research and Development organization (VMRD). This role is embedded within the In Silico Research team in the Automation and Data Science (ADS) group and is pivotal in developing and deploying groundbreaking algorithms, computational tools, and emerging technologies that redefine processes in R&D. The ideal candidate will bring a bold, imaginative approach to problem-solving, with a desire to push the boundaries of what is possible in computational biology and bioinformatics. 

  

The successful candidate will have a proven track record of developing and applying the latest computational biology and bioinformatics solutions in the life sciences field, with expertise in single and multi-omics data analysis, algorithm development, and digital innovation. The role will focus on designing, implementing, and integrating novel and open-source computational tools to address complex biological questions and streamline R&D pipelines. The candidate will work in a collaborative team environment, partnering with biologists, data scientists, front-end developers, and technical teams across the organization to ensure tools are scalable, reproducible, and impactful. 

  

  

Essential Duties and Responsibilities 

·       Envision, design, and integrate advanced algorithms and computational tools, combining creativity with technical rigor to accelerate R&D processes. 

·       Leverage novel approaches and existing open-source technologies to develop solutions that challenge conventional practices and drive innovation. 

·       Collaborate across R&D teams to identify critical challenges and opportunities, actively proposing and pursuing bold ideas for deploying emerging technologies. 

·       Lead efforts to apply cutting-edge technologies to address complex biological questions and research objectives. 

·       Partner with technical teams to optimize, scale, and assess the performance of computational tools and algorithms. 
 

Required Experience & Skills 

·       Ph.D. in Life Sciences, Computational Biology, Bioinformatics, Data Science, or a related field. 

·       A minimum of 2–3 years of postdoctoral or industry experience in relevant biological disciplines. 

·       Proven publication record demonstrating expertise in computational biology, bioinformatics, or data science methodologies. 

·       Proficiency in Python programming and familiarity with best practices for coding and tool development. 

·       Extensive experience in single and multi-omics data analysis, including but not limited to bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, metabolomics, proteomics, and/or genomics. 

·       Experience in the integrating analytics and visualization of non-omics data sources with multi-omics datasets to the understanding systems biology. 

·       Experience applying a variety of machine learning and statistical analyses for prediction and classification projects in biology. Experience working in multidisciplinary teams, including such specialists as biologists, chemists, computer scientists, data scientists, full-stack developers, etc. 

·       Strong communication and presentation skills, with the ability to effectively engage diverse stakeholders across technical and non-technical domains.   

 
 

Preferred Additional Skills 

·       Expertise in other programming or querying languages such as R, JavaScript, or SQL. 

·       Experience working in a Unix environment, with proficiency in high-performance computing systems (e.g., Slurm, SGE) or cloud-based platforms (e.g., AWS, Azure). 

·       Experience developing machine learning (ML) or artificial intelligence (AI) algorithms and tools. 

·       Knowledge of graph and network analysis methodologies. 

·       Familiarity with Git-based workflows, documentation best practices, and reproducible research standards. 

·       Background in full-stack software development for scientific applications. 

 

Full time

Regular

Colleague

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