Strength Through Diversity
Ground breaking science. Advancing medicine. Healing made personal.
The Icahn Institute for Genomics & Multiscale Biology is looking for talented data scientists with the responsibilities and qualifications listed below. At the Icahn Institute, our vision is to transform biomedical research and healthcare delivery into a data-driven, evidence-based, patient-tailored discipline. The Icahn Institute was founded in 2011 to help advance precision medicine with cutting-edge technologies, novel partnerships between the public and private sectors, and world class computational and analytical resources. By maximally leveraging information from patients around the world, we deliver premier precision care optimized for each patient, while discovering breakthrough, next-generation treatments through insights derived from cutting-edge analytics applied to unprecedented amounts of patient-derived data. We promote a core set of values – designed to promote our future vision of team-oriented, data driven global biomedical research: 1) Do good for the patient, 2) Simplify, 3) Share openly, 4) Focus, 5) Synergize, 6) Contributions, not politics, and 7) Deliver.
Role & Responsibilities:
Data Scientists at Mount Sinai work with clinicians, researchers, and engineers to extract value from data. Effective data science is critical to the success of our research efforts and clinical translation, ensuring we make correct inferences from the vast wealth of biomedical data generated at Mount Sinai and across the world.
Data Scientists may work on many of the cutting-edge research areas at Mount Sinai, including:
- Analysis of high throughput genomic, transcriptomic, epigenetic, proteomic, and other omics data in healthy and disease states
- Analysis of multiscale single cell omics data to perform multitissue cellular de novo taxonomy in healthy and disease states
- Scalable machine learning approaches to network and predictive models of biological processes
- Medical record mining using large-scale electronic health record biobanks.
The ideal candidate will have strong analytical and programming proficiencies and proven expertise in high-dimensional data analysis. Specific responsibilities are outline below.
- Apply computational techniques to analyze large-scale biomedical datasets.
- Develop and maintain genetic, genomic, and biological databases to annotate and interpret human genome data.
- Analyze whole genome/exome sequencing and genome-wide SNP array data.
- Create data-driven models and data visualizations for clinical and research work
- Perform rigorous and reproducible data analyses
- Develop projects and work independently on a variety of data analysis projects
- Learn and use bioinformatics tools for processing and analysis of large datasets
- Identify and resolve technical issues and propose upgrades to current software
- Participate in the preparation of manuscripts, grants, and presentations
- Other technical and leadership duties as assigned and commensurate with experience and skills
- Masters, or Ph.D. in Statistics, Biostatistics, Statistical Genetics, Genetic Epidemiology, or other relevant quantitative discipline
- Firm grounding in statistical methods for genome data analysis.
- Experience with biological datasets and next generation sequencing data.
- Experience analyzing large-scale genetic datasets in complex human traits or disease and using main statistical packages for genetic data (e.g. GCTA and SNPtest).
- Experience working with large publically available databases (eg. 1000 Genomes, UK10K, UK Biobank, ExAC, gnomAD, HGMD, TCGA, COSMIC, etc.).
- Outstanding programming skills in at least two of these languages on a Linux environment: Python, R, bash, Perl, Java, and C++.
- Track record of delivering complex scientific projects through high impact factor publications.
- Excellent communication and organizational skills with ability to work to tight timelines, both independently and as part of a multi-disciplinary team.