Bioinformatics Data Analyst

Toronto, Ontario /
Engineering /
About Us
Deep Genomics is a Toronto-based startup company that is building an AI-powered discovery and development platform to significantly expand the universe of medicines available for genetically-defined diseases. Founded in 2015, Deep Genomics brings together a multidisciplinary team of world-leading experts in machine learning, genomics, chemistry, and biology. Together we are on a mission to rapidly discover and develop oligonucleotide drugs for the treatment of patients with severe disorders of the liver, central nervous system, and eye.

Ideal Candidate
We are seeking a highly motivated bioinformatician with strong programming and scripting skills. The successful candidate will work in a multidisciplinary team of biologists and computational scientists and take on tasks spanning analysis of experimental data, genomics data processing, and data visualization. The ideal candidate would have a good understanding of molecular biology, human genetics, and basic statistics.


    • BSc in Computer Science, Bioinformatics or related fields.
    • Understanding of basic concepts in molecular biology and human genetics.
    • Knowledge of Python or R
    • The ability to be productive and successful in a fast-paced and dynamic work environment

Preferred but optional qualifications:

    • MSc in Computer Science, Bioinformatics or related fields.
    • Experience with human genomics data (including next generation sequencing).

What we offer:

    • A highly competitive salary and meaningful equity compensation.
    • Exceptional opportunities for learning and growth.
    • A bright, collegial, highly-motivated team working at the intersection of the most exciting areas of science and technology.
Deep Genomics thanks all applicants, however only those selected for an interview will be contacted. Deep Genomics welcomes and encourages applications from people with disabilities.

Accommodations are available on request for candidates taking part in all aspects of the selection process.