Data Scientist / Sr. Data Scientist

Who We Are At PrognomiQ, we aim to transform healthcare by generating and using systems biology data to develop and commercialize tests for early detection and treatment of cancer and other complex diseases. PrognomiQ leverages leading proteomics technology, including the Proteograph product suite from Seer, as part of a multi-omics platform that provides an unprecedented molecular view of health and disease. We are a team of experienced and accomplished scientists supported by a group of leading investors in healthcare and technology. Would you like to be part of a team that is at the leading edge of molecular data generation and analyses that changes how cancer and other complex diseases are detected and treated? Do you aspire to be on the cutting edge of ‘omics technology and data science development? Are you looking to be part of a world class scientific team striving to bring disruptive solutions to market? Do you thrive in an environment of cross-functional disciplines and innovation? Description Of Role The data science team at PrognomiQ is seeking a Data Scientist to drive and contribute to experimental design, statistical analysis, and research in applying machine learning methods to discover and validate disease-specific signals from a number of different molecular sources for product development. You’ll work within a highly interdisciplinary group, uniting both lab and computational scientists with a broad range of expertise (genomics, proteomics, etc.) in order to implement these methods into novel products that integrate multiple signals into a unified disease detection model. PrognomiQ is combining the breakthrough advances in multi-omic profiling of biological samples with cutting edge AI/ML technologies in order to revolutionize non-invasive diagnostics. Highly motivated experts passionate about the life-saving potential of innovative new diagnostic technologies such as yourself will be critical to our success. Duties This is an on-site or hybrid work position with expectations of being on-site a few times a week. Research and apply novel methods to extract disease-specific features from high-dimensional data, improving classification performance in cancer diagnostic platforms. Support experimental design for product development with statistical requirements based on clinical regulatory guidelines. Drive data analysis with statistical methods and support a high-impact data-driven decision. Work within cloud infrastructure environments, e.g., Amazon Web Services (AWS) to implement code logics and collaborate with software engineers to incorporate codebase to production pipelines as needed. Document results of analyses and investigations in a reproducible manner and communicate insights to both experts and non-experts. Collaborate with cross-functional teams to streamline laboratory workflows through software automation. Requirements: M.S. degree in computer science, data science, mathematics, statistics, bioinformatics, or related fields, or equivalent practical experience (Ph.D. preferred) 3+ years of experience in the related field Strong programming skills in languages like Python, R, C#, JavaScript for data analysis and modeling Experience in working with high-performance computing environments (AWS preferred) Demonstrated skills in proper experimental design, troubleshooting challenges, and interpreting complex data Strong problem-solving skills and ability to work independently and collaboratively across multi-functional teams. Desire to focus on breakthroughs in an exciting, fast-paced startup environment Preferred Experience working in a clinical, diagnostics, or biotech environment. Understanding of statistical methods in regulatory and compliance frameworks such as CLIA, HIPAA, and 21 CFR Part 11. Experience developing codebases and software libraries following industry best practices Equal Opportunity Employment PrognomiQ is an equal opportunity employer that celebrates diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law.

#J-18808-Ljbffr