Request a Partner Login


    Principal/Senior Data Scientist – Full Time | Permanent

    Job Summary

    Are you a self-driven person who loves diving deep into data analysis? Do you enjoy working in a fast-paced, technical environment with new and interesting challenges every day? Are you passionate about using data and technology to improve patient outcomes? If any of these sound like you, read on!
    We are looking to add a Principal or Senior Data Scientist to our high-performing R&D and Data Science/Engineering team. In this role, you will drive the AI/ML strategy in alignment with our business objectives and in collaboration with our teams across research, product development, clinical studies, and sales and operations. You will keep data on the table, identify useful data sources and methods across the organization, and ultimately harvest it to extract business value. You will also be hands-on working on the design, development, deployment, and support of NERv’s AI & ML solutions for early detection of postoperative complications.
    NERv has a flexible, hybrid office/WFH model.

    Job Responsibilities

    • Lead NERv’s data science initiatives.
    • Perform EDA to discover patterns, trends, and insights from extensive sensor data and peripheral data sources.
    • Define analytical experiments in collaboration with R&D teams to validate hypotheses and test potential solutions using statistically sound methods
    • Train, validate, and test predictive and diagnostic clinical models using machine learning / deep learning algorithms for classification, time series analysis and anomaly detection
    • Interface with various engineering and clinical teams to convert domain expertise into production-ready data science models.
    • Work with the development team to improve NERv’s AI/ML solutions.
    • Prepare technical data reports and summaries for regulatory submissions or external presentations on an as-needed basis.
    • Drive and promote the use of innovative approaches within the organization through publications in scientific peer-reviewed journals and presentations at professional meetings.
    • Contribute actively to IP portfolio by internally disclosing inventions and methods, and supporting patent filing activities.
    • Provide support for clinical trial design.
    • Ongoing evolution of models and regulatory conformance verification and validation.

    Required Skills

    • Master’s degree in Computer Science, Data Science, Statistics, or other related fields.
    • 5+ years of experience with Data Science and solving tough data science problems in production.
    • Extensive experience working with Time Series modelling and analysis.
    • Strong knowledge of optimization, classification, clustering, and other ML technologies.
    • Strong experience with Python, especially with its data science libraries.
    • Familiarity with version control tools.
    • Ability to adapt to changing priorities under high-pressure situations.
    • Team player, ability to take feedback from all team members.
    • Ability to interpret and distill complex highly technical (Stats/Math/ML/etc.) concepts and explain it to a wide variety of audiences.
    • Strong research organizational skills.
    • Comfortable working in the Jupyter Notebook/Lab environment.
    • Demonstrable experience in translating research outcomes to commercial products.
    • Demonstrable experience in taking ML models/stacks into viable products.
    • Proven excellence in technical and non-technical oral and written communication.
    • Experience converting raw data into processed, actionable, insightful information.
    • Demonstrable experience in ML Ops.

    Experience working with business stakeholders in understanding data analytics and information needs, and executing on transformation of high-level, abstract data needs into meaningful data management solutions, information, and analysis.

    Preferred Qualifications

    • Experience working with noisy, real-world data from biosensors.
    • Experience with medical device development lifecycle.
    • Experience with the SaMD framework (FDA and Health Canada).
    • Comfortable working with PHI in HIPAA/PHIPA environment.
    • Working knowledge of the healthcare ecosystem (stakeholders, technical jargon, etc.).
    • Familiarity and experience with DataOps.