Responsibilities: Develop analytical models and solutions / production-ready algorithms that solve real business problems, taking into account business needs and technology/operations landscape; lead interaction with internal stakeholders and technology on specific projects and initiatives. Become a domain expert! Apply data science and machine learning techniques to derive business value from the full range of internal and external data sets in a cloud environment. Translate complex data and methodology into strategic, operationally feasible insights and recommendations; automate implementation. Communicate clearly and effectively to technical and non-technical audiences, verbally and visually, to create understanding, engagement, and buy-in. Identify trends and opportunities to drive innovation. Take on ownership of data science projects that drive measurable value for the business. Be a true full-stack data scientist! Basic Qualifications: 3-5 years' post-secondary education or relevant work experience. Additional Qualifications and Skills: Advanced degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline. 2-3 years' experience in developing machine learning models with a track record of creating meaningful business impact and working with multiple stakeholders. 3-5 years' experience with Python and SQL. Experience with cloud computing platforms and tools (prefer AWS, but open to GCP or other). Expertise in multivariate statistical modeling (e.g. clustering, regression, principal components and factor analysis, time-series forecasting, Bayesian methods) and machine learning (Random Forest, KNN, SVM, boosting and bagging, regularization etc.). Experience with translating business use cases into real work experiments, models and insights. #J-18808-Ljbffr