Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

How Will You Make an Impact?
You will join a team of talented engineers and scientists, passionate about bringing actionable insights to genetic testing in research and clinical space. You will work collaboratively in a matrix environment and provide expertise in bioinformatics and expert analysis of data from both next-generation consumable manufacturing and microarray assays. You will help to develop an exciting pipeline of products to meet our mission for quality – right the first time with the customer in mind.
 
What will you do?

• Support new product introductions (NPI) and on-market microarray products.
• Establish and deploy pipelines for process automation and for AI/ML data engineering/model improvement.
• Gather and process data from relevant sources, emphasizing timely execution of development activities with organized documentation of output and releases.
• Work closely with a team of bench scientists to provide interpretation of data and support troubleshooting as required.
• Remain up to date with the latest developments in genomics and biological informatics. You may engage with collaborators or users, and you may attend and present at scientific meetings as appropriate.

 
How will you get here?
 
Education/Experience

• MS degree with 3+ years of industry experience or PhD in bioinformatics, computational biology, statistics, computer science, or biological sciences.
• Proficiency in Python and R, and experience with SQL
• Experience with UNIX/Linux environment
• Knowledge of common sequence repositories and public annotation databases such as dbSNP and OMIM
• Familiarity with statistical methods including significance tests, linear models, ANOVA, time-course analysis
• Familiarity with product development and/or project management is highly desirable
• Must have ability to work independently, with problem-solving and continuous improvement attitude

 
Other competencies

• Knowledge in genetics and/or molecular/chemical biology
• Linux system administration experience is desirable.
• Effective communication skills, especially for presenting scientific results, working collaboratively in a team, and documentation are required.
• Ability to work in a multi-disciplinary and geographically distributed team environment is required.