Data Scientist

Ramona Optics is seeking a Data Scientist in Durham, NC (onsite) to advance cell profiling and computational microscopy. The role focuses on converting large-scale imaging datasets into biological insights while building scalable, reproducible analysis pipelines and backend systems for high-throughput, cell-level analytics.

Responsibilities

• Develop and apply data science and machine learning methods for cell profiling, including segmentation, tracking, and phenotypic analysis from microscopy images.
• Use computational approaches to integrate genomics, transcriptomics, and proteomics data with high-content microscopy datasets for multimodal cellular phenotyping and biological insight discovery.
• Partner with a cross-disciplinary team to design scalable data representations and analysis workflows for high-content microscopy datasets.
• Build and optimize data pipelines for large-scale image analysis, feature extraction, and downstream statistical modeling.
• Design, develop, and maintain backend infrastructure supporting reproducible analysis, as well as storage and retrieval of cell-level data.
• Document models, analysis workflows, and data schemas for internal teams and external collaborators.
• Assess and integrate emerging methods in computational biology, machine learning, and imaging to improve scalability, accuracy, and interpretability.

Requirements

• 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, including 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, such as NumPy, SciPy, scikit-image, PyTorch, TensorFlow, or similar tools.
• Experience working with large scientific datasets and formats including HDF5, Zarr, TIFF, or related serialization and storage systems.
• Knowledge of statistical analysis, model evaluation, and data visualization for biological data.
• Experience with multimodal biological datasets, including genomics, transcriptomics, and proteomics.
• Strong scientific curiosity, problem-solving skills, and attention to biological and computational detail.
• Commitment to clear communication, collaboration, and scientific integrity.
• Experience with multimodal biological data integration.

Technologies

• Python, NumPy, SciPy
• scikit-image, PyTorch, TensorFlow
• HDF5, Zarr, TIFF

Preferred Qualifications

• Master’s or Ph.D degree.
• 5+ years of experience.