Senior Computational Biologist

Cambridge, Massachusetts
Feb 20, 2018
NextGen Bio
Required Education
Masters Degree/MBA
Position Type
Full time

Tango, a 2017 “Fierce 15” company, is an exciting new oncology company launched by Third Rock Ventures, one of Boston’s premier biotech funding groups. Our focus is on identifying synthetic lethal interactions to discover and develop new breakthrough cancer therapies.

Our discovery efforts begin and end with patients. We invert the traditional discovery paradigm by putting patient selection before target identification. We use deep DNA sequencing and CRISPR-based screening to identify novel targets for specific subgroups of cancer patients. Our goal is to leverage the principles of synthetic lethality to find novel weaknesses in cancer cells and use them to provide a roadmap to cures. As we advance our molecules into the clinic, our trials will enroll the patients most likely to benefit from our new treatments; thereby enabling greater speed, success, and impact for those patients.


We are seeking an innovative, collaborative and enthusiastic computational scientist to work on a variety of high-dimensional bioinformatics projects centered on target identification, drug discovery and translational research. The individual will integrate internal and external datasets, including next generation sequence data. The successful candidate will be one who can develop novel methods, analysis strategies and tools to filter and distill multi-dimensional datasets to generate focused hypotheses to drive primary research. A critical component of the job will be the close collaboration with multi-disciplinary internal discovery teams and external collaborators. This individual will be a critical thought leader in the company, collaborating closely with discovery and development scientists.

Job Responsibilities:

    •    Design and evaluate integrative approaches to the analysis of NGS cancer exome and transcriptome data, as well as other high-throughput data types

    •    Apply machine learning/statistical-based approaches to establish and benchmark predictive models of biological/chemical data

    •    Develop innovative, robust, analysis pipelines that can be applied in a research and clinical setting

    •    Develop and contribute to external collaborations and partnerships


Minimum Qualifications:

    •    MS or Ph.D. in Bioinformatics, Computational Biology, Computer Science, or related fields with 3+ years of industry experience; equivalent academic or professional experience will be considered

    •    Expertise in computational biology, genomics and other high-throughput data platforms with an aptitude to apply experimental methods to understand disease biology and drug discovery

    •    Demonstrated ability to formulate and test hypotheses by designing and implementing computational approaches, ability to effectively interpret and communicate conclusions from complex data is essential

    •    Proficient programming skills and computational analysis background

    •    Prioritize and work independently to complete tasks and advance projects with minimal supervision

    •    Ability to work effectively with internal and external collaborators and multidisciplinary teams composed of scientists and non-scientists to translate emerging research to guide internal programs

    •    Proficient written and verbal communication skills, particularly of complex information and concepts

    •    Working knowledge of oncology and/or immunology preferred

Preferred Qualifications:

    •    Significant experience in the analysis of high-throughput DNA and RNA high-throughput sequencing data, including alignment, quality measurements, variant calling, fusion discovery and transcript quantification

    •    Fundamental statistics and machine learning applications to life sciences

    •    Predictive modeling, benchmarking

    •    Experience with mining public data sets, such as TCGA

    •    Technical proficiencies should include:

    •    Linux in a grid and/or cloud environment, experience with cloud computing preferred

    •    Familiarity and experience applying statistical fundamentals

    •    Experience with R, PERL or Python, SQL are highly desirable

    •    Distributed computing

    •    Identify partners/consultants to complement internal bioinformatics efforts

    •    Creative, innovative thinking