Arrowhead Pharmaceuticals, Inc. (Nasdaq: ARWR) is a clinical stage biopharmaceutical company that develops medicines that treat intractable diseases by silencing the genes that cause them. Using a broad portfolio of RNA chemistries and efficient modes of delivery, Arrowhead therapies trigger the RNA interference mechanism to induce rapid, deep, and durable knockdown of target genes. RNA interference, or RNAi, is a mechanism present in living cells that inhibits the expression of a specific gene, thereby affecting the production of a specific protein. Arrowhead’s RNAi-based therapeutics leverage this natural pathway of gene silencing.
Arrowhead is focused on developing innovative drugs for diseases with a genetic basis, typically characterized by the overproduction of one or more proteins that are involved with disease. The depth and versatility of our RNAi technologies enables us to potentially address conditions in virtually any therapeutic area and pursue disease targets that are not otherwise addressable by small molecules and biologics. Arrowhead is leading the field in bringing the promise of RNAi to address diseases outside of the liver, and our clinical pipeline includes disease targets in the liver and lung with a promising pipeline of preclinical candidates.
Arrowhead’s corporate headquarters is in Pasadena, CA with research and development teams in Madison, WI & San Diego, CA, and a state of the art manufacturing facility in Verona, WI. Our employees are nimble, science-driven innovators who are collaborating to bring new therapies to patients in need.
The Position
We are seeking a highly motivated and skilled Data Engineer to join our Research Informatics team within R&D. The successful candidate will play a key role in supporting Translational Genetics, Computational Chemistry, and AI/ML-driven discovery with software, AI tools, data requests, and building data infrastructure and pipelines that support immediate and longer term needs.
This role will actively support Arrowhead’s AI-enabled discovery initiatives by enabling high-quality, well-governed datasets for machine learning and advanced analytics. Responsibilities include preparing data for AI/ML workflows, supporting model training environments, and evaluating AI-powered tools (including LLM-based systems) to accelerate research insights, automation, and decision-making across R&D.
The successful candidate will understand data and software needs for R&D teams, identify and access process gaps and opportunities to speed up research and optimize research results. This role also contributes to evaluating and deploying AI-enabled tools that enhance scientific productivity and insight. The best candidate will also design and implement robust data pipelines and architectures that integrate experimental and computational data across the research organization. A strong background in scientific informatics platforms (e.g., LIMS/ELN such as Benchling) and a passion for FAIR data principles are essential.
Responsibilities
- Support R&D teams with their day-to-day software, AI tools and data integration needs.
- Evaluate, prototype, and adopt emerging technologies that advance data engineering, scientific AI, and research informatics capabilities.
- Partner closely with Discovery Chemistry and Biology teams to ensure seamless data flow between experimental, analytical, and predictive workflows.
- Develop and standardize data models and architectures to support research data management, metadata, and governance.
- Build and manage integrations across scientific informatics platforms, including ELN, CDS, and analytical systems, to unify experimental and computational datasets.
- Design, develop, and maintain scalable, reliable data pipelines to support R&D data integration, processing, visualization, and advanced analytics.
- Influence architectural decisions that optimize data accessibility for AI development, analytics, and visualization tools.
- Contribute to the vision, strategy, and roadmap for R&D data engineering, architecture, and data governance.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Bioinformatics, or a related field.
- 4+ years of professional experience in data engineering or data science, preferably within biotech, pharmaceutical, or scientific research environments.
- Familiarity with data modeling, metadata management, data lineage, and data governance best practices.
- Strong proficiency in Python, SQL, Git, and modern data engineering practices.
- Experience with AI/ML frameworks and tooling (e.g., PyTorch, LangChain, or custom ML/AI pipelines).
- Hands-on experience designing ETL/ELT workflows and managing both structured and unstructured data.
Preferred
- Experience supporting AI/ML workflows, including data preparation, curation pipelines, and model training environments.
- Understanding of scientific data domains such as omics, assays, screening, or chemical data.
- Advanced skills in data analysis, exploration, and visualization tools.
Arrowhead provides competitive salaries and an excellent benefit package.
All applicants must have authorization to work in the US for a company.
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Arrowhead Pharmaceuticals Pasadena, California, USA Office
225 South Lake Avenue, Suite 1050, Pasadena, CA, United States, 91101
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