About the Role
We are seeking an experienced Data Scientist with a strong background in computational biology and clinical data analysis. In this role, you will develop advanced analytical models and pipelines to extract insights from biological and clinical datasets, empowering scientists, clinicians, and researchers with data-driven solutions for understanding complex disease mechanisms and therapeutic strategies.
You'll work at the intersection of computational biology, clinical informatics, and deep learning, developing scalable workflows that transform multi-modal biological and clinical data into actionable insights for scientific discovery and clinical decision-making.
Location: California (Remote options available)
Key Responsibilities
• Develop algorithms and scalable machine learning, deep learning pipelines for analyzing omics data, biological pathways, disease interactions, and multi-modal biological data prediction and integration
• Apply data mining, predictive modeling, and optimization techniques to large-scale omics, clinical, and biomedical datasets using machine learning and deep learning methods
• Build and maintain scalable data pipelines, automated model training frameworks, and production-ready analytics tools for biological and clinical applications
• Translate research and clinical requirements into technical solutions and collaborate with bioinformatics, clinical research, and software engineering teams to integrate models into workflows
• Evaluate and implement emerging technologies in AI, deep learning, and computational biology to enhance model performance and biological discovery
• Communicate complex analytical results to scientific and clinical stakeholders through data storytelling, visualization, and publication-ready reports
Required Experience & Qualifications
- Advanced degree (Ph.D. or M.S.) in Computational Biology, Bioinformatics, Computer Science, Statistics, or related field (or equivalent experience)
- 5+ years of experience in data science, computational biology, bioinformatics, or AI/ML applications in life sciences
- Strong communication skills with client-facing experience and ability to translate complex analytical findings into actionable insights for scientific and clinical teams
- Proficiency in Python, with extensive experience in libraries such as Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow, including expertise in sophisticated deep learning architectures (CNNs, RNNs, Transformers, GANs)
- Strong understanding of biological pathways, molecular interactions, and disease mechanisms, including genomics, proteomics, and systems biology concepts
- Experience with biological data types including RNA-seq, single-cell sequencing, proteomics data, and clinical datasets (EHR, clinical trials)
- Expertise in statistical methods including hypothesis testing, survival analysis, experimental design, and multivariate analysis for biological research
- Proficiency with cloud platforms (AWS) and scalable data pipelines for large-scale biological data processing
What Makes This Role Unique
As a Sr. Data Scientist, you’ll be at the forefront of integrating machine learning, biological knowledge graphs, and intelligent agents to tackle complex problems in biology and medicine. This role goes beyond developing predictive models—you’ll be building dynamic systems that reason, adapt, and interact with scientific data to uncover meaningful insights.
Your work will directly influence how scientists explore biological pathways, how clinicians understand disease progression, and how researchers generate and validate new hypotheses. You’ll help shape a new generation of intelligent tools that don’t just analyze data—they actively guide scientific discovery through continuous learning and contextual understanding.
What We Offer
- Competitive salary, equity package, and performance-based bonus
- Comprehensive Health, dental, vision insurance, and 401(k) retirement plan
- Flexible work arrangements and remote options
- Access to state-of-the-art hardware, cloud platforms, and AI research infrastructure
- Meaningful work transforming the future of healthcare
About GNQ
GNQ InSilico is a cutting-edge genomics-driven platform company dedicated to transforming and de-risking the drug development process. Our innovative approach uses advanced AI to simulate therapeutic behavior on diverse human genomic profiles, enabling life sciences companies to optimize clinical trial design and bring safer, more effective drugs to market faster.
