Data Scientist
Ramona Optics · Durham, North Carolina, United States
Biotechnology Research · 11-50 employees
About the role
Develop and apply machine learning methods for cell profiling, segmentation, and phenotypic analysis from microscopy images. Collaborate with cross-disciplinary teams to build scalable data pipelines and integrate multimodal biological datasets.
What they look for
Requirements
Requires a Bachelor's or Master's degree in Data Science, Computer Science, or a related field with at least 2 years of experience. Candidates must have strong proficiency in Python and hands-on experience with microscopy or imaging data analysis.
Full description
About the role
We are seeking a data scientist to advance our cell profiling and computational microscopy platform, transforming large-scale imaging data into biological insight. You will work closely with biologists, microscopists, and software engineers to design and deploy data-driven methods that extract meaningful cellular phenotypes from complex image data. In this role, you will help build scalable data analysis pipelines and backend systems that enable high-throughput cell profiling, reproducible science, and efficient data exploration. We are looking for a data scientist who is excited to operate at the intersection of imaging, machine learning, and biology, helping lay the foundation for scalable cell-level analysis.
Key responsibilities
- Develop and apply data science and machine learning methods for cell profiling, segmentation, tracking, and phenotypic analysis from microscopy images.
- Apply computational methods to integrate genomics, transcriptomics, and proteomics data with high-content microscopy datasets to enable multimodal cellular phenotyping and biological insight discovery.
- Collaborate with a cross-disciplinary team to design scalable data representations and analysis workflows for high-content microscopy datasets.
- Build and optimize data pipelines that support large-scale image analysis, feature extraction, and downstream statistical modeling.
- Contribute to the design and maintenance of backend infrastructure that supports reproducible analysis, storage, and retrieval of cell-level data.
- Document models, analysis workflows, and data schemas for internal teams and external collaborators.
- Evaluate and integrate emerging methods in computational biology, machine learning, and imaging to improve scalability, accuracy, and interpretability.
Qualifications
Required:
- Bachelor’s or Master’s degree in Data Science, Computer Science, Biomedical Engineering, Computational Biology, or a related field (or equivalent experience).
- 2+ years of experience
- Strong proficiency in Python, with experience in scientific computing, data analysis, and machine learning workflows.
- Hands-on experience analyzing microscopy or imaging data, particularly for cell profiling, segmentation, tracking, or feature extraction.
- Familiarity with image analysis and machine learning libraries (e.g., NumPy, SciPy, scikit-image, PyTorch, TensorFlow, or similar).
- Experience working with large scientific datasets and data formats such as HDF5, Zarr, TIFF, or related serialization/storage systems.
- Knowledge of statistical analysis, model evaluation, and data visualization for biological data.
- Experience working with multimodal biological datasets, including genomics, transcriptomics, and proteomics data.
- Strong scientific curiosity, problem-solving skills, and attention to biological and computational detail.
- A commitment to clear communication, collaboration, and scientific integrity.
- Experience with multimodal biological data integration.
Preferred:
- Master’s or Ph.D degree
- 5+ years of experience