Senior Data Scientist - AI & Genomics

April 3

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DNAstack

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DNAstack is a technology company that provides a software platform, Omics AI, designed to connect, protect, and enable AI-powered discoveries across federated networks of omics and health data. Their software suite allows data custodians and researchers to share and analyze omics data while complying with international privacy standards and open industry standards by the Global Alliance for Genomics & Health. DNAstack's tools facilitate the development of federated data networks that promote collaborative research in areas like infectious diseases, neuroscience, and genomics. The platform emphasizes privacy, security, and interoperability by design.

genomics • bioinformatics • cloud • big data

11 - 50 employees

Founded 2013

🤖 Artificial Intelligence

🧬 Biotechnology

⚕️ Healthcare Insurance

💰 Pre Seed Round on 2019-01

📋 Description

• Develop and apply AI-powered data science methods for analyzing large-scale genomic datasets in a federated environment. • Design, train, and validate machine learning and deep learning models for genomics, including variant classification, functional annotation, and disease risk prediction. • Collaborate with partners in academia and industry to create models that process and harmonize diverse genomics datasets. • Apply large language models (LLMs) and generative AI for automated annotation, scientific literature mining, and variant impact prediction. • Utilize federated learning frameworks to train AI models on distributed genomic data while ensuring privacy compliance. • Support the development of data harmonization and feature engineering pipelines to enhance AI model performance across genomic datasets. • Communicate complex AI-driven genomic analyses clearly to technical and non-technical stakeholders. • Stay current with emerging AI and deep learning techniques for genomics, participating in open-source initiatives and advancing industry best practices.

🎯 Requirements

• Master’s degree or PhD in data science, computational biology, bioinformatics, AI/ML, biostatistics, or a related field—or equivalent industry experience. • 4+ years of hands-on experience applying data science and machine learning techniques to genomics datasets. • Strong experience implementing AI-powered bioinformatics tools and applying machine learning techniques to genomic analysis. • Proficiency with deep learning models for genomics such as AlphaFold, ESMFold, OpenFold, DeepSEA, and Enformer. • Experience with LLMs for genomic applications, including automated annotation and text-based variant interpretation. • Strong programming skills in Python (preferred), R, or Julia, with experience using AI/ML libraries such as TensorFlow, PyTorch, or scikit-learn. • Expertise in working with large-scale genomic datasets, including WGS, WES, RNA-seq, and methylation data. • Familiarity with cloud computing (GCP, AWS, or Azure) or HPC environments. • Experience leveraging federated learning and privacy-preserving AI for genomic data sharing. • Strong interpersonal and communication skills—able to translate between technical, scientific, and clinical domains. • Statistical and visualization skills for exploring -omics datasets.

🏖️ Benefits

• Remote-friendly with flexible hours • High impact work • Three weeks vacation • Unlimited sick days • Competitive benefits package • Career development and learning support