Translational Bioinformatics Scientist

Responsibilities : Collaborate with Global Translational Medicine Leads to design and execute analysis plans that address key translational research questions from asset teams. These may include indication and/or patient selection, biomarker discovery (pharmacodynamic, prognostic, and predictive, and disease biomarkers) Identify and leverage relevant public and proprietary datasets to support translational objectives, and effectively communicate findings and insights to cross-functional asset teams. In alignment with current and future portfolio needs, partner with Global Translational Bioinformatics Leads to develop and implement novel analytical methodologies and platforms, such as spatial transcriptomics workflows and integrated data portals, to enable cutting-edge translational research. Support the ingestion, curation, and archiving of large-scale omics and imaging datasets generated from Astellas-sponsored clinical trials and academic collaborations. Requirements Qualifications: Required Ph.D. in computational biology, bioinformatics, or other biomedical sciences with 4-6 years’ experience in applying bioinformatics or computational approaches to drug discovery/development, preferably in a biopharma setting Strong hands-on experience with Python, R, or similar languages commonly used in bioinformatics or image analysis Demonstrated expertise in analyzing multi-omics and clinical data to support research into disease mechanisms, patient stratification and biomarker discovery Experience in at least one of the following domains: advanced spatial transcriptomics analytics (oncology), advanced imaging analytics (oncology), or ophthalmology clinical imaging biomarker analytics Strong problem-solving mindset and willingness to work collaboratively in cross-functional clinical research environments Good communication skills, especially in explaining technical concepts to non-technical stakeholders. Eager to learn new technologies and passion in translational / clinical research Preferred Exposure to deep learning frameworks (e.g., PyTorch, TensorFlow) and experience training or fine-tuning models on oncology imaging (H&E, IHC, mIF, etc) or omics data is a plus Some experience in ophthalmic imaging analysis (OCT, FAF, etc.) is a plus but not required Salary Range $130K - $170K (NOTE: Final salary could be more or less, based on experience) Benefits: Medical, Dental and Vision Insurance Generous Paid Time Off options, including Vacation, Sick time, plus national holidays including Heritage Days, and Summer and Winter Breaks 401(k) match and annual company contribution Company paid life insurance Annual Corporate Bonus and Quarterly Sales Incentive for eligible positions Long Term Incentive Plan for eligible positions Referral bonus program

Created: 2026-02-19