Principal Applied Researcher Machine Learning
Collective Medical – Engineering /
PointClickCare is the leading North American cloud-based healthcare software for the acute and long-term and post-acute care markets. For over 20 years, the company has held the same vision – to help the world care for vulnerable populations. Since its inception, PointClickCare has grown exponentially with over 1,700 employees today all working towards impacting the lives of millions. Recognized by Forbes as one of the Top 100 Private Cloud Companies and acknowledged by Waterstone Human Capital as Canada’s Most Admired Corporate Culture, PointClickCare leads the way in creating cloud-based software. With its recent acquisition of Collective Medical, PointClickCare solidifies its position as a high growth healthcare software provider, serving over 21,000 long-term and post-acute care providers and over 1,300 hospitals. Their shared mission to support vulnerable populations is allowing PointClickCare and Collective Medical to connect disparate points of care at scale faster than anyone else in the market.
Reporting to the Vice President, Advanced Technology, you will be a member of the Advanced Technology team at PointClickCare. You are an exceptionally talented Principal Applied Researcher with a strong Machine Learning background, looking to make a difference solving critical customer and business challenges in the dynamic healthcare market by building cutting-edge solutions leveraging multiple kinds and sources of data with a variety of machine learning and natural language based predictive models and other solutions to be deployed at scale.
You thrive on solving complex machine learning modelling challenges, applying creative and pragmatic solutions--from framing problems to preparing data, to selecting appropriate techniques, algorithms and features to prototyping, building and evaluating models that will truly transform healthcare and enable our customers to deliver better care to vulnerable populations.
· You will be applying ML and/or NLP/NLU techniques to develop machine learning models and related solutions which may involve working with data scientists and machine learning experts, domain experts, customers, UI/UX designers and product leaders as well as backend engineering and infrastructure teams and operations to integrate the models into successful end user experiences in the context of a large-scale cloud-based SaaS production environment.
· Design, build and evaluate predictive models, classifiers, recommenders, summarizers or other machine learning based models to be deployed into production environments, including research and experimentation to select and tune appropriate approaches, algorithms and frameworks.
· Perform or assist in data collection, data cleaning, data analysis, algorithm selection or design, feature engineering, model training and evaluation, and partnering with engineering on development and deployment of ML services at scale.
· As a principal applied researcher, you will bring technical mentorship on advanced analytics, data science, statistical and machine learning methods and technologies to the team, and help the organization develop new capabilities for innovative solutions.
· You will have substantial independence and responsibility from day one.
· PhD or comparable level of experience in Computer Science, Math, Physics, Engineering or a related field.
· Expert level practical experience applying machine learning and related techniques to solve real-world problems involving predictive analytics, content extraction, classification, summarization, recommendation or other applications.
· Experience building and deploying machine learning models into large-scale SaaS products, including familiarity with industry standard software development concepts such as approaches to scaling issues, version control, CI/CD pipelines, and security.
· Expert level experience with at least one area of machine learning or natural language processing. This includes hands on work performing standard tasks (e.g. feature selection, language modeling) and techniques (e.g. transfer learning, transformers, ensemble models, etc.) as well as applying specific models and tools.
· Solid understanding and experience with multiple kinds of models and machine learning approaches such as logistic regression, Random Forest, Bayes networks, active learning, machine teaching, reinforcement learning, deep learning and other models or approaches.
· Proficiency in Python and one or more of C, C++ or Java.
· Experience doing data engineering for ML applications, including exposure to database systems and proficiency with SQL.
· Proficiency building models from big data using modern machine learning packages, models data analysis stacks such as NumPy, SciPy, Scikit-learn, fastText, Pandas, Keras, Tensorflow, PyTorch, CNTK and NLTK.
· Accomplished and curious problem finder and problem solver, able to think both creatively and methodically, including strong fundamentals in optimization, problem solving, model building and evaluation.
· Strong interest in applying machine learning to healthcare related problems and data
· Experience working with large data sets using big data processing frameworks (e.g. Azure Data Lake, HDFS/Hadoop, Spark or other cluster computing/MapReduce frameworks)
· Happy doing whatever data wrangling and cleaning are necessary to create solutions, but also looking for ways to make model development processes more efficient over time.
· Experience using public cloud infrastructure for building, evaluating and deploying machine learning models (Azure, AWS, Google Cloud)
· Exceptional communication skills and comfortable working on a distributed team
It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact email@example.com should you require any accommodations.