> Markdown version of [/jobs/ext/1850231-data-scientist-ii](https://www.wearedevelopers.com/jobs/ext/1850231-data-scientist-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist II - **Company:** Fred Inc - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $104,458.0 - $165,090.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Bioinformatics, Cloud Database, Computational Biology, Data Cleansing, Data Governance, Data Transformation, Data Visualization, Python (Programming Language), Machine Learning, Natural Language Processing, Standard Sql, Git, Information Technology - **Published:** July 3, 2026 - **Apply:** https://kshealthjobs.net/jobs/rss/22396014/data-scientist-ii ## About the Role * B.A., B.S. in computational biology, biostatistics, computer science, data science, biophysics, bioinformatics, or a related field. * Minimum 5 years of experience in data science, bioinformatics, or related disciplines. + Graduate degrees can apply towards this minimum (M.A./M.S. = 2 years, PhD = 4+ years), * Graduate degree in epidemiology, biostatistics, statistics/mathematics, public health, computational biology, bioinformatics, biology, or a related field. * Proficiency in R and/or Python programming. * Strong SQL and experience working in cloud-based data ecosystems. * Experience working with the OMOP common data model and OHDSI tools. * Demonstrated knowledge of machine learning and deep learning. * Demonstrated rigor and reproducibility through well organized and well documented code and/or committed to a public code repository. * Experience using Git in a collaborative setting. * Experience working with standardized medical vocabulary and ontologies (ICD-10, SNOMED, RxNorm, etc.) * Experience with data governance processes for working with regulated data (HIPAA, GDPR, etc.). * Strong oral and written communication skills, and the ability to prioritize written documentation. * Excellent interpersonal and communication skills with audiences with a wide range of data expertise. * A functional understanding of medical oncology, cancer epidemiology, or immunotherapy. * Proficiency in natural language processing tasks and tools, especially with clinical text. ## Description * Participates in collaborative data science projects with academic researchers, oncologists, statisticians, and other partners. * Develops reproducible statistical analyses and machine learning models for topics such as: cohort identification, clinical characterization, and patient-level prediction. * Thinks critically and communicates clearly throughout the data science lifecycle (problem formulation, data cleaning, EDA, analysis, evaluation, and communication of results). * Creates data visualizations, reports, queries, and summaries to communicate findings to collaborators. * Supports development and growth of our common data model (OMOP) for real-world, observational health research through investigating data quality, conducting exploratory analysis on new data sources, and making recommendations for data transformation requirements. * Identifies, understands and creates multimodal data packages integrating clinical and research laboratory data to create comprehensive descriptions of patient journeys. * Collaborates with the translational data science team to develop templates, packages, and documentation for the data science community at Fred Hutch and self-serve analytics users. * Ensures analyses meet a high standard for methodological rigor and stays current in methodology for real-world evidence studies. * Complies with data governance and data privacy policies. ## Related Videos - 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