Staff/Sr Staff Data Scientist

About Countable Labs

At Countable Labs (formerly Enumerix), we’re reimagining the future of genomics—and we’d love for you to be a part of it! As the innovators behind our groundbreaking Countable PCR platform, we’re building tools that make a real impact in precision medicine. We’re a fast-growing startup fueled by innovation, collaboration, and a mission-driven spirit. If you’re ready to roll up your sleeves, build something from the ground up, and help shape the future of genomics, we want you on our team!

Role overview

We’re seeking a Staff / Sr Staff Data Scientist to join our data and software team. In this role, you’ll lead the development of analytical, visualization, and QC modules that transform large-scale 3D imaging datasets into clear, actionable biological insights.

You’ll apply your expertise in image analysis, signal and data processing, statistical modeling, and machine learning to improve data quality, interpretability, and scientific impact.
A key part of this role involves building data analysis and visualization tools that empower scientists to easily explore, analyze, and interpret their data — combining technical depth with a strong understanding of user needs from a scientist’s perspective.

You will also play a key technical leadership role by mentoring junior team members, reviewing code and analyses, and establishing best practices for software quality, testing, and production reliability.

This is a high-impact, interdisciplinary role at the intersection of data science, software engineering, and genomics, shaping the analytical foundation of Countable’s next-generation platform.

What You’ll Do

• Design and implement algorithms for processing, analyzing, and interpreting large 3D imaging datasets at scale.
• Apply signal and data processing techniques—including noise reduction, normalization, and filtering—to enhance data quality and consistency.
• Use advanced statistical methods and machine learning (e.g., clustering, dimensionality reduction, multilabel classification) to uncover structure and insights in high-dimensional data.
• Define and compute intuitive, quantitative QC metrics that help scientists assess data quality, reproducibility, and confidence.
• Collaborate with product management to design intuitive, customer-facing data reporting and visualization features that make complex results easy to interpret.
• Build robust data analysis and visualization tools that enable scientists to explore, interpret, and communicate their data effectively.
• Collaborate closely with scientists and cross-functional teams to validate algorithms, incorporate feedback into analytical tools, refine workflows, and integrate modules into production pipelines.
• Develop and maintain well-tested, production-quality code, with emphasis on reliability, reproducibility, and maintainability.
• Mentor and support junior team members, fostering technical excellence, rigor, and collaboration across the team.
• Champion best practices in data integrity, testing, and analytical rigor throughout the organization.

What We’re Looking For

• PhD (or equivalent experience) in Computational Biology, Bioinformatics, Computer Science, Applied Physics, or a related quantitative field.
• 5+ years of industry experience developing and delivering data-driven products for customers, ideally in life sciences, genomics, or computational imaging.
• Proven expertise in image analysis and processing, applied to large or complex scientific datasets.
• Strong foundation in statistics, signal processing, and data normalization techniques.
• Demonstrated ability to evaluate, structure, and interpret complex, noisy datasets with strong analytical judgment and data intuition.
• Experience designing visualization tools and reports that make scientific data accessible and actionable.
• Proficiency in Python and MATLAB; experience with C# is a plus.
• Experience writing robust, production-grade analytical code and integrating algorithms into software products.
• Excellent communication and collaboration skills across interdisciplinary teams.
• Thrives in a fast-paced startup environment, balancing scientific depth with product impact.

Nice-to-Haves

• Experience with deep learning frameworks (PyTorch, TensorFlow) for image or signal analysis.
• Familiarity with fluorescence imaging, optical microscopy, or other quantitative imaging techniques.
• Experience with spatial or single-cell genomics or other high-dimensional biological data.
• Experience developing interactive visualization tools (e.g., Plotly, Dash, Bokeh, PyQt).
• Knowledge of workflow orchestration, data versioning, or database management systems.