Bioinformatics & ML Scientist
Remote
Full Time
#Engineering
#Machine Learning
#Bioinformatics
#Python
#Data Analysis
At Nomic, we are on a mission to make biology easier to measure. We created nELISA, the world’s most advanced high-throughput proteomic platform, by combining DNA nanotechnology, high-dimensional flow cytometry, and machine learning. Since our start at McGill University, we have grown to support six of the top ten pharmaceutical companies, having processed over 60 million proteins from more than 400,000 samples. We are currently looking for a Senior Bioinformatics & ML Scientist to join our team in a full-time, remote capacity. In this role, you will lead the development of our analysis pipelines and machine learning models, helping our partners turn complex proteomic data into actionable scientific discoveries.
Responsibilities
- Design and refine robust pipelines for proteomic and transcriptomic data, focusing on quality control, normalization, batch correction, and data integration.
- Develop and prototype machine learning models for target discovery, functional genomics, and phenotype classification, working alongside engineering teams to bring these solutions into production.
- Translate complex customer needs into clear, high-impact insights and intuitive features for our Nomic Portal, while providing expert guidance on perturbation screens and multi-omics analysis.
Requirements
- A PhD or equivalent professional experience in Bioinformatics, Computational Biology, Machine Learning, or a related quantitative discipline.
- At least 5 years of hands-on experience building bioinformatics or machine learning pipelines using Python or R.
- Proven track record of analyzing proteomics and transcriptomics datasets, particularly within the context of target discovery or functional genomics.
- Strong statistical expertise and a deep understanding of data-wrangling, quality control, and normalization techniques.
- Demonstrated ability to balance technical, hands-on coding work with mentorship and cross-functional collaboration.
- Excellent communication skills, with a history of contributing to scientific publications or technical content.
What we offer
We are proud to support a flexible work environment and offer the following benefit:
- Remote work flexibility.
