Job Description :
Title: Data Scientist Location: Vancouver, BC Duration: Contract Job Description: The ideal candidate is adept at using small, medium, and large sets of data to find opportunities for product and process optimization, and in using statistical tests and models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining and statistical analysis methods, defining models, and implementing both proof of concept and production statistical/analytical pipelines, using/creating algorithms, and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be highly collaborative and comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in small and medium data sets and working with stakeholders to improve business outcomes. Provide consultation and oversight in the optimization and improvement of product development, marketing techniques and business strategies by proposing and defining solutions and implementation roadmaps for statistical pipelines, including data collection, model specification, algorithm configuration, system configuration and tuning requirements, fitting, forecasting, prediction, and reporting components that address customer business problems. Define and implement project roadmaps for exploratory data analysis, data mining, data collection, preprocessing and business analyses. Propose new statistical models and data science solutions that are grounded in the business space Prepare and present information using data visualization techniques Implement, model, and oversee best practices, including repeatable and reproducible analytic workflows and SDLC practices Design experimental and innovative features/signals that might improve a statistical pipeline 7+ years of experience manipulating data sets and building statistical models, has a PhD (preferred) or Master's in Statistics, Biostatistics, Applied Mathematics, Mathematics, or other quantitative field. Able to self-learn new techniques from textbooks and research papers Competency with one or more computational languages (e.g. R, S-Plus, SAS, SPSS, JMP, or Python) and SQL Demonstrated aptitude for computer programming and SDLC