Remote Senior Data Scientist, Computational Biology

Summary

Join a multi-disciplinary team of experts at Valo Health to accelerate the creation of life-changing drugs for patients faster.

Requirements

• BS+4, MS or PhD + 1 years experience in bioinformatics, computational sciences, computational biology, or related fields (e.g., genetics, molecular biology)
• Experience in modeling multi-omic (2 or more: genomic, transcriptomic, proteomic, and/or metabolomic) data with statistical/machine learning methods & biological network analyses towards understanding biological functions and disease processes
• Experience with high-dimensional omics data and their challenges, including biological, experimental, and computational sources of noise & variance, and approaches to address multi-collinearity
• Strong analytical, problem-solving, and communication skills, including facility with Rmarkdown and/or Jupyter Notebooks for communicating reproducible results
• Ability to also condense, summarize, and synthesize results into informative and actionable presentations to scientific audiences as demonstrated by original peer-reviewed publications in respected journals, oral presentations at scientific meetings
• Experience in R and/or Python, including familiarity with code, data, and model versioning
• Experience with OMICs data processing workflows (e.g., nextflow, snakemake), evaluating QC metrics and adjusting for batch effects, and working in cloud environments (e.g., AWS)
• Undergraduate or graduate level course work in at least two of the following: Cell Biology, Microbiology, Developmental Biology, Physiology, Immunology, Genetics, Epidemiology, Evolution, Biochemistry, Organic Chemistry, History of Science

Responsibilities

• Integrate ‘omics data from diverse public and proprietary sources into our data platform
• Ensure high quality data through bioinformatics pipelines, QC checks, data normalization, and correction for batch effects
• Perform DEG, GSEA, pathway/MOA, and network biology analyses to advance preclinical target identification, validation, and drug discovery programs
• Publication quality data visualization & impactful, cross-disciplinary communication
• Provide expertise in biological systems, statistics, and computational biology
• Contribute to the identification of novel targets and clinical biomarkers
• Be a dynamic and active team member, providing regular updates of your work and feedback regarding that of your colleagues

Preferred Qualifications

• Domain knowledge in cardiovascular disease and its co-morbidities (e.g., obesity, diabetes, and inflammation)
• Experience with network biology (eg, WGNCA) approaches
• Familiarity with public data sources (eg, GEO, CMAP/LINCS, etc)