Scientist, Computational Chemist & MLOps Engineer
About The Position
Arrowhead Pharmaceuticals, Inc. is a commercial stage biopharmaceutical company focused on developing medicines that treat intractable diseases by silencing the genes that cause them. The company utilizes a broad portfolio of RNA chemistries and efficient modes of delivery to trigger the RNA interference mechanism for deep and durable knockdown of target genes. Arrowhead's RNAi-based therapeutics leverage this natural pathway of gene silencing to address diseases with a genetic basis, typically characterized by the overproduction of one or more proteins involved in disease. The company's technologies enable it to potentially address conditions in virtually any therapeutic area and pursue disease targets not addressable by small molecules and biologics. Arrowhead is a leader in bringing RNAi to address diseases outside of the liver, with a clinical pipeline including targets in the liver and lung, and a promising pipeline of preclinical candidates. The corporate headquarters is in Pasadena, CA, with R&D teams in Madison, WI & San Diego, CA, and a manufacturing facility in Verona, WI. Employees are described as nimble, science-driven innovators collaborating to bring new therapies to patients. 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.
Requirements
- Bachelor’s or Master’s degree in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Data Science, Applied Mathematics, or related field (Scientist I)
- 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
- Advanced degree (PhD preferred) or equivalent industry experience (Scientist III)
- Demonstrated history of leading computational projects independently (Scientist III)
- Strong background in applied statistics, predictive modeling, and experimental data interpretation (Scientist III)
- Experience mentoring scientists or leading technical initiatives (Scientist III)
- Ability to translate ambiguous scientific problems into robust computational solutions (Scientist III)
Nice To Haves
- 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
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)
Benefits
- Competitive salaries
- Excellent benefit package
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
