Ref No.: 18-01333
Location: Cambridge, Massachusetts
Start Date / End Date: 05/22/2018 to 12/21/2018
The clinical genetics analyst will be responsible for executing quality control and data transformation steps on next-generation sequencing (NGS) variant data ahead of transfer to clinical databases. The analyst will be responsible for reviewing all data for correctness and consistency and for resolving technical problems that arise. The candidate will have familiarity with common data outputs from NGS, the associated quality metrics, experience in Python and R, and deep commitment to quality and strong attention to detail. The candidate will be responsible for executing work in a reproducible manner and with a high level of documentation. As this position will require coordination and collaboration with other groups such as data management, project management and scientific research, the candidate must have strong communication skills.
Essential Job Functions and Responsibilities
Collaborate with internal and external teams to draft, review and sign-off on data transfer specifications
Execute quality control and data transformation scripts for NGS data in R and Python
Review output of quality control and data transformation scripts, escalate issues with data set quality to appropriate teams and coordinate resolution ahead of transfer to clinical databases and collaborators
Coordinate and execute data transfers

Desired Skills and Experience
Familiarity with wide range of variant data from NGS sequencing
Basic understanding of NGS genome reference files and formats
Basic understanding of molecular biology
Knowledge of quality metrics associated with NGS variant calls
Demonstrated proficiency in Python and R
Ability to communicate clearly with stakeholders from diverse technical and scientific backgrounds
Strong attention to detail and commitment to high quality work
Ability to set and meet timelines
Proactive mindset to troubleshooting and root cause analysis
Pluses
Previous experience with quality control of NGS data sets
Previous experience in a clinical or production environment
Familiarity with Extract-Transform-Load tasks and data transfer specifications
Exposure to continuous integration and version control systems, such as Jenkins and Bitbucket
Experience with Laboratory Information Management Systems and Electronic Lab Notebooks

Bachelor’s degree in biology, chemistry, computer science, statistics, or related fields