Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global healthcare and life sciences organization is advancing drug discovery and development through the integration of artificial intelligence, data science, computational biology, and software engineering. Its research organizations leverage advanced computational models and large-scale biological datasets to accelerate scientific discovery and develop innovative medicines.
Key Responsibilities
- Establish, maintain, evaluate, and productionize reproducible and scalable analytical workflows for proteomics and genomics data.
- Develop libraries, visualizations, and software tools that support biological data analysis and quality control.
- Enable scientists to interrogate complex biological datasets and make data-driven decisions relevant to research and drug development.
- Facilitate data reuse, multimodal analysis, and AI/ML initiatives through standardized data formats and repositories.
- Collaborate closely with computational scientists to understand analytical requirements and translate them into reusable software components.
- Evaluate and integrate open-source, commercial, and internally developed technologies into reliable scientific applications.
- Develop software throughout the complete development lifecycle, including planning, implementation, testing, release, and maintenance.
- Build scientific workflows and tools that make biological data accessible to both computational systems and human users.
- Work with Software Engineers, Computational Biologists, and Data Scientists on interdisciplinary projects.
- Apply modern software development practices and AI-assisted technologies throughout the development process.
- Work with MCPs, REST APIs, and other modern programmatic interfaces.
- Manage FAIR data, track data lineage, ensure data quality, and improve data discovery.
- Break complex scientific and technical problems into manageable software components and deliver solutions independently or collaboratively.
Required Qualifications
- PhD in Software Engineering, Computer Science, Bioinformatics, or a related discipline with at least 2 years of relevant experience in a clinical, academic, or commercial environment.
- Alternatively, a Master’s degree or equivalent qualification with at least 5 years of relevant experience.
- Experience analyzing complex biological datasets using modern data science frameworks.
- Strong knowledge of major analytical tools and statistical methods used across different omics modalities.
- Expert knowledge of proteomics analysis with the ability to identify, diagnose, and address unexpected or unreliable results.
- Demonstrated experience delivering software projects throughout the full development lifecycle.
- Strong understanding of modern software development practices.
- Experience using AI-assisted technologies throughout software development workflows.
- Comfortable working with MCPs, REST APIs, and modern data science interfaces.
- Extensive experience managing FAIR data, data lineage, data quality, and data discovery.
- Ability to break down complex problems into reusable software components.
- Ability to work independently and collaboratively across interdisciplinary teams.
- Strong organizational skills and the ability to manage multiple concurrent projects in a fast-paced environment.
Preferred Qualifications
- Experience with the Bioconductor and Tidyverse ecosystems.
- Experience with RMarkdown or Quarto.
- Experience with Shiny and Plumber deployment.
- Experience with Python technologies such as Pandas, Polars, Streamlit, or FastAPI.
- Experience working across both R and Python environments.
- Previous experience in life sciences, pharmaceutical research, or drug development.
What to Expect
- A highly collaborative and dynamic research environment focused on accelerating scientific discovery through purpose-built solutions.
- Access to large datasets, biological samples, and advanced computing resources.
- Access to state-of-the-art technologies and pioneering scientific research.
- Opportunities to participate in seminar series featuring academic and industry scientists.
- A campus-like working environment that supports a healthy work-life balance.
- Mentored opportunities to develop and strengthen professional skills.
Disclaimer
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- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
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