Sr. Computational Biologist/Data Scientist


Fabric Genomics is building a team of the best and brightest to help shape the future of personalized medicine. Our mission is to help clinicians apply the most relevant information from personal genomes to improve medical outcomes. Come join us to change patient care through big data and genomics.

We are looking for an experienced, self-motivated, and hands-on computational data scientist to joint of Science team. You will focus on identifying appropriate datasets and developing statistical and machine learning approaches to analyze large genomic data sets. You must be passionate about extracting quantitative insights from data sets and apply them to clinical settings. Your knowledge of the life sciences and genomics areas will enable you to identify the proper solutions and new applications. You will work closely with other data scientists, bioinformaticians, software engineers, technical executives, clinical collaborators and customers in developing novel techniques for analyzing genomic data.


    • Develop statistical and machine learning algorithms on genome data.
    • Aggregate and analyze genomic and other types of clinical data to find novel insights.
    • Apply machine learning techniques to automate genomic data analysis.
    • Develop analysis strategies and visualizations to help clinicians and scientists interpret genomic data.
    • Develop code to implement analysis workflows in a robust and reproducible fashion.
    • Follow processes to improve transparency and reliability of applications, reducing project risks for on-time milestones.
    • Educate other scientists, engineers and management on the methods developed and how they apply to the subject domain and customer needs.    


    • PhD with strong background in computational biology, statistics, computer science, applied mathematics, or related field.
    • Minimum 3-5 years of experience in computational biology, data science, or bioinformatics positions, ideally in life sciences industry; relevant post-doctoral/academic experience can be considered.
    • Ability of independent thinking, problem solving, and appreciation of mathematics and computer science methods to solve multidisciplinary problems.
    • Knowledgeable in genomics, sequencing applications, clinical tools and databases a major plus.
    • Proficiency in Python, Scala, Java or C/C++, programming languages and tools essential. 
    • Experience with data wrangling, statistical methods, and machine learning toolkits such as Numpy, R, scikit-learn, Tensorflow, Keras, or PyTorch is necessary. Exposure to deep learning methods a plus. 
    • A publication track record on computational biology/bioinformatics/computer science is desirable.
    • Experience developing software for deployment on Linux/Unix and cloud services, and with parallelization and distributed computation tools such Spark is desirable.
    • Team player with excellent communication skills.
Candidates located in the San Francisco Bay Area are strongly preferred. Candidates must have pre-existing US work authorization.