Epoch Biodesign is a well-funded, venture-backed start-up using biology to make every type of plastic recyclable - starting with nylon.
Using a unique combination of AI, synthetic biology and green chemistry, we are scaling enzymatic recycling in order to transform currently unrecyclable plastics and textiles into new, virgin-quality materials. Our technology yields substantial reductions in carbon emissions with disruptive unit economics, preventing waste from entering landfill or the environment, allowing us to solve this very urgent challenge.
With our pilot plant already processing nylon 6,6 waste, we will imminently complete construction on our larger demo facility. This site will produce material destined for use in garments made by some of the world’s biggest fashion, sportswear and luxury brands, and also in components for some of the world’s largest car companies.
The Role
As a Scientific Data Engineer at Epoch you will support and advance Epoch's computational infrastructure by building, maintaining and improving the data pipelines that underpin our R&D activities. Working closely with computational and lab biologists, you will gather requirements, prototype solutions and develop robust, reproducible pipelines - ensuring that data flows reliably from instrument to insight. Experience in the life sciences and an ability to learn quickly and adapt to changing requirements is essential. Your core activities will include:
* Managing, maintaining and bug-fixing our existing sequence analysis pipeline, with a focus on next-generation sequencing data (Oxford Nanopore experience strongly preferred)
* Managing and extending our analytics data-processing pipeline, including ingesting data from instrument computers into cloud infrastructure and configuring automated triggers for downstream processing
* Taking computational pipelines built at prototype stage by other team members and transitioning them into robust, reproducible, production-ready systems using containerised deployments (Docker)
* Acting as primary contact with lab biologists to understand the nature of their data, their analytical methods and their requirements for processing, access and visualisation
* Training colleagues in the use of developed tools and pipelines
* Liaising with our external IT provider to ensure company devices are properly set up, maintained and secured
Essential Qualifications & Experience
* A degree in bioinformatics, computer science, or a similar numerical field
* Strong technical background in Python and common scientific/data libraries (e.g. NumPy, SciPy, Pandas)
* Hands-on experience with next-generation sequencing data analysis, with Oxford Nanopore experience strongly preferred
* Demonstrated experience with Google Cloud Platform (GCP) or Amazon Web Services (AWS), including cloud-based pipeline orchestration
* Proficiency with Docker and containerised deployment workflows
* Experience with automated testing practices
* Experience with environment and dependency management tools (e.g. Conda, Mamba)
* Proficiency with Git and version control best practices ```
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