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Job opportunities / Metabolomics Data Analyst - Madison, WI
The data analyst will be engaged in experimental design and analysis of large scale LC-MS based metabolomics experiments for the identification of biomarkers, creation of predictive models, and biological networks based on interpretation of the results. The position will involve working on both client-based projects as well as internal Stemina platform and discovery efforts. The candidate should have a track record demonstrating the ability to be inquisitive, self-motivated and self-directing, to develop realistic project plans with timelines, and to solve problems using the application of scientific theory.
Essential Job Duties and Responsibilities
• Design and implement the analysis for targeted and discovery based metabolomic experiments.
• Assist in design and execution of scientific metabolomics experiments in collaboration with bioinformatics, analytical chemistry and cell biology staff.
• Evaluate metabolomics and other ‘omics’ data within a biological context to explain the significance of the results.
• Perform comparative analyses of mass spectrometer derived metabolomic data.
• Develop predictive models based on the results of metabolomics experiments.
• Work closely with biologists and analytical chemists in updating and utilizing multiple sources of biological data.
• Follow established SOPs to analyze targeted and discovery based metabolomic experiments
• Write grant applications in collaboration with other scientific staff.
• Keep and maintain accurate and detailed records of all research and experiments performed.
• Maintain current technical procedures and quality assurance.
• Attend staff and lab meetings.
Qualifications:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education and Experience:
• Ph.D in Statistics, Biostatistics, Mathematics, Computational Biology or, a molecular biotechnology or related discipline with a research focus in the area of statistical or mathematical analysis of ‘omics’ data.
• A minimum of 3 years post graduate experience designing, analyzing, and interperting large "omics" based data sets preferably in the areas of metabolomics, proteomics, or gene expression.
• Demonstrated experience in the generation of predictive models from experimental "omics" data utilizing univariate, multivariate, and machine learning methods.
• Experience with network or pathway based interpretation of "omics" data.
• A background in biology or biochemistry, specifically understanding of the metabolic pathways is desired, but not required.
• Broad understanding of bioinformatics tools used for analysis of metabolic, gene expression, and protein expression data.
• At least 3 years’ experience using statistics scripting languages such as R to perform data analysis.
Knowledge, Skills and Abilities Required:
• Effective interpersonal, verbal and written communication skills, including public-speaking and presentation skills.
• Ability to maintain high level of confidentiality.
• Ability to effectively communicate with all levels of the organization.
• Demonstrated ability to work well independently as well as a part of a diverse team.
• Ability to maintain experimental consistency.
• Demonstrated ability to work well under pressure and manage multiple tasks with constantly changing priorities.
• Demonstrated ability to troubleshoot problems and recommend resolutions.
• Knowledge of implementation and design of state-of-the-art algorithms for metabolomic, genomic and metagenomic analysis.
• Advanced analytical, organizational, and record-keeping skills.
• Proficient computer skills: Proficiency with the Windows and Linux operating systems and MS Office.