Senior Scientist I/II, Computational Biology

About Sail:

The Role:

The Sail Biomedicines Data Science team is looking for a talented Computational Biologist seeking an environment where they can make an impact. As a key member of the Sail Data Science Team, the Senior Scientist II will lead efforts in a cross-disciplinary team of experimental, computational, and machine learning scientists and engineers to drive the development and extension of Sail’s AI-driven programmable medicine platform, thereby pushing a new class of RNA-medicines towards the clinic.   

Responsibilities:

• Strategic Pipeline Development and Optimization: Oversee the design, implementation, and continuous enhancement of advanced, scalable computational pipelines for a range of high throughput sequencing data types (e.g., RNA-Seq, Amplicon-Seq, scRNA-Seq) and other large-scale biological data. Innovate and drive improvements in pipeline architecture to meet evolving research demands and industry trends. 

• Comprehensive Documentation and Knowledge Sharing: Develop and manage detailed documentation integrated with our digital data backbone for pipeline workflows, analytical methods, and results. Ensure that documentation promotes reproducibility, transparency, and effective knowledge transfer across scientific and technical teams. 

• Excellence in Quality Assurance: Lead the development and enforcement of rigorous quality control measures to ensure superior data accuracy, integrity, and reliability. Address and resolve complex issues related to data quality, pipeline performance, and system robustness with a strategic approach. 

• Enterprise Data Management: Facilitate structured data capture, management, and integration at an enterprise level. Enhance data accessibility, utility, and governance across diverse scientific and research platforms. 

• Advanced Data Analysis and Interpretation: Direct data analysis using advanced statistical and computational methods to evaluate and derive actionable insights from complex datasets across various scientific disciplines. Guide the interpretation and application of results, ensuring relevance to experimental methodologies and biological contexts, and inform strategic decision-making. 

• Cross-Disciplinary Collaboration: Build and maintain strategic partnerships with multidisciplinary teams, including but not limited to computational biology, bioinformatics, genomics, systems biology, and data science. Drive the advancement of research programs and technology platforms from development through clinical and commercial applications. Communicate complex concepts effectively to diverse audiences. 

• Project and Timeline Management: Supervise and manage multiple high-impact projects, ensuring alignment with strategic goals, adherence to timelines, and delivery of results. Provide guidance and oversight to ensure project success and timely completion. 

Qualifications:

• PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, Physics, or related field, with industry experience (4+ years), preferably in leadership roles with a track record of collaborating with various scientific disciplines. 

• Expertise in Advanced Programming and Computational Tools: Proficiency in relevant programming languages (e.g., Python, R), advanced statistical analysis tools, and command line tools for NGS analysis. Proven ability to develop and optimize sophisticated computational solutions across diverse data types. 

• Extensive Experience with Modern Technologies: Over 5 years of experience with version control systems (e.g., Git), reproducible computing (e.g., Docker), workflow management systems (e.g., Nextflow, Snakemake), and cloud computing platforms (e.g., AWS) or HPC environments.  

• Proven Leadership in Computational and Analytical Projects: Demonstrated success in leading large-scale computational and analytical projects within multidisciplinary teams, with experience in mentoring and developing junior staff. 

• Advanced Data Analysis Across Scientific Disciplines: Extensive experience in analyzing complex datasets from genomics, transcriptomics, proteomics, lipidomics, and other multi-omics fields. Skilled in applying advanced statistical and computational methods. 

• Strategic Data Exploration: Evaluate datasets with strategic and innovative approaches and leverage data to enhance core informatics workflows and drive research and operational excellence. 

• Exceptional Communication and Advocacy Skills: Strong ability to articulate complex methodologies and analyses to audiences with varying levels of technical expertise. Advocate for and implement digital-first and data-driven strategies across the organization. 

• Innovation and Methodology Development: Proven ability to develop new methodologies, tools, and visualizations, with a focus on advancing research capabilities and operational efficiency.