Data Scientist II, Molecular Biology
About The Position
Evozyne is an AI-native biotech company building a new way to design therapeutic proteins. Our generative AI platform was purpose-built to create entirely novel proteins that expand what’s possible beyond traditional drug discovery. We are applying this platform to develop transformative therapies for serious diseases with significant unmet need, working at the intersection of AI, biology, and protein engineering to solve complex scientific problems that conventional approaches cannot easily address. Reporting to the Senior Director, Data Science, you will execute the analytical strategy for our drug discovery programs, encompassing experimental design, data synthesis, and featurization. You will partner closely with experimental scientists to understand assay design, wrangle multi-assay datasets, build decision-grade plots and summaries, and translate results for audiences from bench scientists to leadership. You’ll incorporate the latest advances in biological assay developments and database infrastructure to streamline program analytical processes, and your work will directly support experimental decision-making and generate high-quality datasets for model training (GenAI) for the design of novel synthetic biomolecules.
Requirements
- A PhD in a relevant scientific/or technical discipline with 0-2+ years relevant postdoctoral or industry experience, or a Master's degree with 4+ years of experience.
- 2+ years of experience working in a cross-functional, collaborative scientific environment, such as in an academic lab, pharmaceutical company, and/or biotech.
- Extensive experience working in an experimental scientific discipline, designing and executing experiments.
- Advanced proficiency in preprocessing, analyzing, and cataloging high-throughput molecular biology or biochemistry datasets in Python.
- Familiarity in database organization and management.
Nice To Haves
- Expertise in ML and deep learning implementation, preferably in PyTorch or TensorFlow, is preferred.
Responsibilities
- Analyze, synthesize, and catalog experimental data across various data modalities to provide insights and optimization approaches.
- Collaborate extensively with experimental scientists - asking questions, reflecting on objectives, and agreeing on success criteria before executing.
- Own the development of reproducible pipelines to synthesize high-throughput experimental results into features amenable for training deep learning models.
- Draw upon their experience in programming to maintain and update the company’s data processing and ingestion software infrastructure.
- Deliver analyses and decision-grade visualizations that directly inform next-step experiments, assay optimization, or go/no-go decisions.
Benefits
- Relocation assistance is not available for this position.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
