Research, design, develop, test, and deploy machine learning systems. Research, develop, and enhance models using machine learning algorithms. Utilize statistical, natural language processing to transform unstructured and structured data into normalized, structured data, and create insights. Analyze large datasets and build models using advanced statistical methods. Implement algorithms and software needed to perform analyses (eg. software R, Python, and SQL). Collect, combine and clean, and convert data for analysis (eg. variable identification, univariate analysis, bi-variate analysis, missing values treatment, outlier treatment, variable transformation, variable creation). Responsible for ensuring business intelligence data model code is reviewed, and standard documentation is provided before releases are made public. Coordination and completion of data projects on time within budget and within scope. Oversee all aspects of data mining and analytics projects. Set deadlines, assign responsibilities and monitor and summarize progress of project. Prepare reports for upper management regarding status of project. Serve as key point of contact for business stakeholders. Collaborate across organizational teams with business owners and executives to facilitate self-service data exploration. Collaborate across organizational teams with business owners and executives to automate existing metrics and reporting. Develop, deploy and maintain dashboards, reports, and other analytical services for business owners and executives; Includes managing key business metrics in company's business intelligence platform following data governance best practices, as well as building story-telling visualization using design-thinking concepts. Develop and maintain standardized reporting data models within company's enterprise data environment following data governance best practices. Partner with other data scientists and data engineers to incorporate new data sources within company's enterprise data environment following data governance best practices. Design, develop and maintain key business metrics in companies business intelligence platform following data governance best practices. Develop data pipelines for training, scoring, and monitoring established statistical and machine-learning models. Develop, deploy, monitor and maintain best-in-class predictive models for forecasting, process automation, segmentation, and other critical business functions. Partner with Data Engineering team to define, standardize and document business rules that need to be applied to the source data to drive data analysis and reporting. Partner with Data Engineering team to define and build dimensional models in DWH to drive all reporting and analysis of company-defined KPIs and associated metadata.
U.S. or Foreign Masters or equivalent in the physical sciences, engineering, or statistics including coursework in Calculus, Linear Algebra, Data Statistics and Analysis, atomistic modeling, numerical methods, and the application of statistics and/or numerical modeling; and 1 year experience as Data Scientist or related occupation involving the application of statistics, applied mathematics, computer science, physical sciences or a similar technical field.