Head of Computational Biology at Stealth Startup in San Francisco, California

Posted in Other 3 days ago.

Type: full-time





Job Description:

The Role

We are looking for a senior data scientist with a strong technical background to lead our advanced algorithms team. You will translate product concepts into technical problem formulations and guide your team of data scientists and ML engineers in developing and productionizing solutions. The ideal candidate has great mathematical intuition, deep knowledge of single cell/spatial omic data, and experience in implementing modern computational tools.

Key Responsibilities

+ Explore translational value of new data types and conceptualize data pipelines in coordination with the executive and commercial teams.

+ Help identify and source diverse training data for developing robust predictive models.

+ Enhance the computational performance, accuracy, and scalability of our spatial omics analytics platform.

+ Expand the platform's capabilities by designing and incorporating new analytical methods, multimodal data integration, and new machine learning architectures.

+ Formulate and structure complex biological and clinical problems into precise, solvable algorithmic challenges.

+ Systematically mine analytical outputs and latent space representations for novel biological insights, ontological frameworks, and actionable opportunities.

+ Establish rigorous validation frameworks and benchmark predictions against empirical datasets, continuously iterating to improve model robustness and real-world applicability.

+ Stay at the forefront of advances in single-cell and spatial omics data science, proactively identifying cutting-edge methods and technologies to integrate into our workflows.

Qualifications

+ PhD or MS in Computer Science, Computational Biology, Machine Learning, Applied Mathematics, or similar.

+ At least 2 years of intensive hands-on experience analyzing single-cell and spatial omics data.

+ Proven track record developing computational pipelines for single-cell or spatial omics datasets.

+ Experience in evaluating, adopting, and customizing advanced algorithms including deep learning, probabilistic modeling, and unsupervised learning techniques for biological data.

+ Creative problem-solving abilities, coupled with strong communication skills, enabling effective direction of multidisciplinary teams of scientists and engineers.

What We Offer

+ Competitive salary and stock options.

+ Customary employee benefits.

Our Culture

We are mission-driven, tech optimists developing a disruptive platform at the convergence of compute and bio.
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