The Position

We are seeking a highly motivated computational scientist to join our research organization and contribute to machine learning–driven drug discovery efforts. This role will focus on data engineering, statistical modeling, bioinformatics, and scientific software development supporting internal therapeutic design programs. The ideal candidate combines strong quantitative reasoning with practical software engineering skills and is comfortable operating independently in a Linux-based research computing environment.

This position may be filled at the Scientist I - III level depending on experience and qualifications.

Responsibilities

• Develop and apply statistical and machine learning models to experimental datasets
• Design, maintain, and optimize scientific databases and data processing pipelines
• Build reproducible computational workflows for bioinformatics and drug discovery applications
• Analyze high-dimensional biological datasets and communicate findings to multidisciplinary teams
• Contribute production-quality Python code and maintain version-controlled scientific software
• Operate effectively in Linux/HPC environments, including remote systems and cloud-based infrastructure
• Write clear, maintainable, and testable scientific code
• Debug complex computational and data issues independently
• Operate effectively in terminal/Linux-native workflows
• Apply statistically rigorous thinking to experimental interpretation
• Maintain reproducibility and software engineering discipline in research environments
• Partner with scientists across biology, chemistry, bioinformatics, and computational research groups
• Support development of internal computational platforms and modeling infrastructure
• Document workflows, analyses, and software according to reproducible research standards
• Mentor junior team members and contribute to technical best practices (Scientist II/III)

Requirements

Scientist I

• Bachelor's or Master's degree in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Data Science, Applied Mathematics, or related field
• Strong programming experience in Python
• Experience working in Linux command-line environments
• Foundational understanding of statistics and machine learning methods
• Experience handling structured and unstructured biological datasets
• Familiarity with source control tools such as Git

Scientist III (In addition to the above)

• Advanced degree (PhD preferred) or equivalent industry experience
• Demonstrated history of leading computational projects independently
• Strong background in applied statistics, predictive modeling, and experimental data interpretation
• Experience mentoring scientists or leading technical initiatives
• Ability to translate ambiguous scientific problems into robust computational solutions

Preferred

• Experience with predictive modeling and/or deep learning methods
• Familiarity with modern ML tooling and model evaluation methodologies
• Experience in therapeutic design, RNA biology, genomics, or laboratory experience
• Experience with bioinformatics workflows and sequence-based analysis
• Experience working with large-scale biological or omics datasets
• Experience with distributed computing systems
• Experience operating in collaborative software development environments