Scientist I/II, Data Science

About Sail:

The Role:

The Sail Biomedicines Data Science team is looking for a talented Data Scientist seeking an environment where they can make an impact. As a key member of the Sail Data Science Team, the Data Scientist (I/II) will work as part of 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:

• Develop and Optimize Pipelines: Design, implement and maintain scalable computational pipelines for the processing and analysis of high throughput sequencing data (e.g. RNA-Seq, Amplicon-Seq, scRNA-Seq).
• Quality First: Design and implement quality control measures to ensure the accuracy and reliability of sequencing data. Troubleshoot and resolve issues related to data integrity, quality, and pipeline performance.  
• Data Analysis: Conduct secondary data analysis leveraging statistical methods to interpret complex datasets, facilitate understanding (e.g. connection to experimental methodologies / biology), and drive strategic decisions. Own ensuring that collaborators understand the properties of the data, including highlighting limitations and opportunities for improvement.  
• Documentation: Clearly document pipeline workflows, analysis methods and results to enable reliable and reproducible computing strategies for standardized and interactive code.
• Digital First: Facilitate the generation and capture of enterprise data in a structured manner.
• Collaboration: Partner with a cross-disciplinary team to support the growth of our platform and the advancement of programs to the clinic. Excellent written and verbal communication skills with the ability to clearly communicate messages across diverse audiences.
• Manage Timelines: Handle multiple projects, ensuring timely delivery of results. 

Qualifications:

• PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, Physics, or a related field with experience in industry a plus
• Proficiency in a relevant programming language (e.g. Python, R) and standard command line tools for NGS analysis.
• Experience (2+ years) with version control systems (e.g. Git), reproducible computing (e.g. Docker), workflow management (e.g. Nextflow, Snakemake) and effectively leveraging resources from HPC/cloud computing platforms (e.g. AWS)
• Demonstrated success leading computational efforts within a multidisciplinary team.
• Experience with genomic and statistical data analysis.
• An inquisitive approach to exploring and evaluating data for use in core informatic workflows.  
• Ability to communicate complex methodologies and analyses to audiences of varying technical levels / knowledge. Effectively operate within, and advocate for, a digital-first environment.
• Experience working with additional ‘omics data (e.g. lipidomics, proteomics) is a plus.  
• Demonstrated ability to develop new methodologies and visualizations is a plus.