New York, NY

Description

We are looking for a highly creative and innovation-driven Bioinformatics Analyst to work with Envisagenics data engineers and bioinformatics scientists to develop, maintain and analyze the company’s proprietary database. Envisagenics is a highly multidisciplinary group combining software engineers, UX designers, computational biologists and pharma partners. We seek team players eager to integrate a founding team whose vision is finding better drug targets to cure yet incurable diseases using biological Big Data. We are looking for experts in transcriptomics, genomics, big data integration and interpretation. The candidate will be responsible for building pipelines and creating tools to manage large volumes of sequencing data and will assist with generating and assessing meta-data to support internal R&D efforts. The ideal candidate will have experience with analysis of large datasets, knowledge of tools and biological databases, SQL knowledge, strong programming skills and proficiency in parallel and cloud computing.

Responsibilities

• Work with scientists and engineers to facilitate development of Envisagenics proprietary database.
• Responsible for setting up an analysis pipeline to process raw instrument output and conduct downstream bioinformatics analysis.
• Responsible for mapping to reference genomes, de novo assembly, cancer variant detection, expression analysis, ChIP-seq etc.
• Conduct feature engineering to build on the platform’s machine learning capabilities
• Conduct objective evaluation and comparison of bioinformatics tools.
• Work collaboratively with other team members to implement QC assessment and standardized analysis protocols for each of the projects as appropriate.
• Keep updated on relevant scientific literature and product updates to help improve data analysis methods.
• Remain up to date with the cancer genomics field by attending seminars, lectures, and training courses to learn new computational biology skills or programming languages/techniques.
• Support preparation of manuscripts and grant applications.
• Performs other duties as assigned.

Qualifications

• MS in Bioinformatics or related discipline
• Must be independent and strategically minded, team-oriented
• Experience with PostgreSQL, MySQL, MongoDB or similar.
• Experience with cloud services such as Google Cloud, Microsoft
• Azure or Amazon AWS
• Strong programming with R/Bioconductor, Python, Perl, C++,
• UNIX, Bash scripts.
• Experience with Grid Engine, Hadoop, Spark
• Experience with building / supporting / using bioinformatics pipelines.
• Experience with statistical and mathematical modeling with
• genomic/transcriptomic data.
• Experience with open source tools for CLIP-Seq and RNA-Seq data analysis (Samtools, Bedtools, read aligners, quantitative tools).
• Experience with machine learning, Bayesian statistics, clustering/classification, multivariate analysis, network analysis and visualization.
• Experience developing and integrating data analysis tools to manipulate large datasets.
• Familiarity with public biological data repositories (TCGA, GTEx, ENCODE, etc.)
• A track record demonstrating scientific creativity, collaboration, and independence.

Preferred Skills

• Proficient written, communication and presentation skills.
• Ability to work in an Agile environment.

About Us

Envisagenics is a bioinformatics startup developing cloud-based solutions to leverage biomedical big data and accelerate R&D therapeutics through machine learning. Envisagenics is a spin-off from Cold Spring Harbor Laboratory, a biomedical research institute ranked #1 worldwide for scientific impact in the field of genetics. Envisagenics’ core technology, SpliceCore was developed by our CTO while at Cold Spring Harbor Laboratory in Dr. Adrian Krainer’s Laboratory, a leader in the RNA splicing field who was also a developer of Spinraza (Nusinersen), the first FDA-approved drug to treat children with Spinal Muscular Atrophy. The mission of Envisagenics is to materially advance the world’s ability to cure diseases, discovering new and more efficient drug targets through the analysis and integration of genomic data alongside our pharma partners.