Senior Mass Spectrometry 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. To accomplish this, we are leveraging leading proteomics technology, including the Proteograph product suite from Seer Bio, in combination with other multi-omics assays to develop unprecedented molecular views 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? If you answer “yes” to either of these questions, let us know by applying!
Description of rolePrognomiQ is leveraging game-changing advances in proteomic methods (Seer Bio’s Proteograph Suite) with cutting edge next generation sequencing (NGS) technologies in order to revolutionize non-invasive diagnostics. Highly motivated experts passionate about creating disruptive diagnostic technologies for early disease detection are valued and critical to our success.
- Analyze proteomics, lipidomics, or metabolomics mass spectrometry data to uncover disease-specific signals.
- Work with the assay development team in order to refine assay chemistry in order to improve signal and reduce noise.
- Design and develop mass spectrometry data processing pipelines and algorithms.
- Evaluate, research and develop analysis methods for mass spectrometry data and apply them to generate insights.
- Collaborate with a cross-disciplinary team of laboratory scientists, analytical chemists, automation engineers, and clinical researchers to design experiments and optimize our mass spectrometry workflows.
- Contribute reproducible, reusable, and robust code to the internal codebase.
- Document results of analyses and investigations in a reproducible manner.
- Communicate insights to both experts and non-experts via presentations and publications.
- Ph.D. in bioinformatics, biostatistics, computational biology, or related discipline. 3+ years relevant industry experience would be preferred.
- Expertise in mass spectrometry-based protein quantification and identification as well as the current computational tools required to process and analyze MS data.
- Demonstrated skills in proper experimental design, troubleshooting challenges, and interpreting as well as innovating on complex mass spectrometry data.
- Expertise in developing novel machine learning approaches to biological data as demonstrated by high-impact publications or product launches would be preferred.
- Proficiency in at least one general purpose coding language such as Python or R. Experience in working with common machine learning software (e.g., scikit-learn, Tensorflow, Keras, etc.) and high-performance computing environments (e.g., AWS) would be preferred.
- Proficiency in general statistical methods as commonly used in the field.
- A record of achievement as evidenced by quality publications or positions of increasing responsibility in industry.
- Excellent communication and presentation skills and a desire to work towards larger team goals
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. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship.