At Bionano Genomics®, we are committed to unlocking understanding of genome biology to advance the promise of genomics in areas including cancer and human disease, agricultural bioengineering and genome discovery. Our optical genome mapping and analysis tools help researchers see true genome structure to fill in what’s missing from sequencing-based data.
At Bionano, we are invested in the success of our customers and users around the world, and are dedicated to supporting them with the tools, resources and support they need to achieve their goals and make a real impact on improving quality of life for all.
Bionano Genomics is looking for a talented, versatile Data Analyst, Clinical Affairs to work on analysis of data generated from a fluidic nanochannel device that enables next-generation optical genome mapping applications. This position requires the analysis of data generated, manage data processing, organization the results, generation of reports in spreadsheet and presentation slides. The candidate must be organized and have excellent communication skills to work closely with molecular biologists and computer scientists at Bionano Genomics.
Primary Duties and Responsibilities:
- Perform data analysis on public and proprietary genomics data.
- Analyze results generated from clinical/research projects according to scientific goals.
- Prepare reports for director sign off.
- Participate in clinical affairs meetings.
- Engage with customers to confirm project detail, goals and progress.
- Present results to customers, collaborators, at scientific meetings, and in peer reviewed publications.
- A minimum of 2 years relevant industry or research experience in genomics or human genetics.
- Experience with one or more of the following: Shell, Python/Perl, R.
- Ability to multi-task and work in a fast-paced environment.
- Experience working with high throughput platforms such as microarrays and NGS and their application to de novo assembly and structural variation analysis.
- Experience with analysis of human genetics/genomics data, including prioritization and identification of disease-driving variants.
- Experience in working with high throughput platforms such as microarrays and NGS and their application to de novo assembly and structural variation analysis.
- Experience with basic molecular biological lab techniques related to the preparation and analysis of genomic DNA such as enzymatic reactions, PCR, and PFGE.
- Education and Experience Requirements:
- Minimum Master’s degree in an area related to genomics, computational biology or bioinformatics.