Senior Bioinformatics Scientist, Research and Early Development

About the position Responsibilities • Design, prototype, and analyze performance of novel statistical/machine learning models. • Investigate data in model free contexts integrating fundamental statistical and visualization techniques and biological knowledge to derive insights. • Apply modeling and model free approaches to large-scale genomics and epigenomic NGS data. • Collaborate with Technology Development scientists on designing experiments to assess and improve assay performance. • Work with cross-functional teams to discuss immediate and long-term product strategy. • Participate in brainstorming sessions and collaborative efforts within a highly interactive work environment. • Communicate analysis results to stakeholders across computational and experimental teams. • Develop reproducible analyses for research and development activities. • Provide written documentation and specifications. Requirements • Dedicated to making a difference in a rapid-paced, collaborative, startup-like environment. • Ph.D. in computational biology, bioinformatics, genomics, statistics, computer science, machine learning, or related fields. • Strong background in statistical fundamentals and analysis, including inference approaches and iterative model development, and hypothesis testing. • Experience developing and implementing novel methods, and going beyond packaged algorithms. • Experience with analysis of genomic and/or epigenomic NGS data. • 5+ years experience in industry/academia post-graduation. • Ability to design and execute analyses in an open-ended, data-limited setting. • Experience visualizing complex experiments to derive biological insights. • Proficiency with a high level scripting language (e.g. Python, R). • Proficiency with Linux command-line and version control tools (git and GitHub). • Excellent communication skills in an interdisciplinary environment. Nice-to-haves • Background in cancer biology or molecular biology. • Experience analyzing external genomic/epigenomic datasets (e.g. TCGA, ENCODE). • Familiarity with high-performance computing infrastructures (e.g. SGE, Spark). • Experience leveraging AWS-based services (e.g., EC2, S3) to speed analyses. Benefits • Hybrid Work Model with defined days for in-person/onsite collaboration and work-from-home days. • Base salary range for this full-time position is $157,100 to $212,040. • Flexible work-life balance. Apply tot his job Apply tot his job Apply tot his job