Data Scientist Ramona Optics Durham, NC Job Details Full-time 1 day ago Qualifications AI models Genomics Data visualization software proficiency Image processing Data Integration (Data management) AI platforms (beyond public GPTs) Computational framework Machine intelligence Feature extraction Statistical modeling Cell imaging Machine learning libraries Model evaluation Machine learning frameworks Bioinformatics data analysis Data visualization projects Segmentation analysis Data analysis software Full Job Description About Ramona At Ramona, we've reimagined microscopy for the modern researcher. Our Multi-Camera Array Microscope (MCAM™) is the first of its kind to offer video-speed capture of cellular detail across an entire well plate. By equipping scientists with unprecedented speed, precision, and insight, we're on a mission to advance human health and insight through computational microscopy. 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