Builds and validates predictive models of a known issue with some assistance, utilizing large scale data from multiple data sources and ensures adoption of the model. Drives continuous improvement to existing models and reviews other Data Scientists' models.
Uses data science techniques to create data-driven solutions for various business use-cases
Develops a minimal viable product to meet business needs while resolving any issues that may arise.
Analyzes and mines very large quantities of data across a small set of domains in collaboration with other data scientists to find patterns and insights utilizing statistical software.
Familiar with project management principles.
Writes Python code.
Collaborates with other data scientists to analyze potential new data sources for availability and quality, and integrates with existing databases. Performs data cleaning and analysis.
Interprets, communicates, and presents analytic results to business stakeholders and process owners.
Collaborates with fellow data scientists and periodically interacts with business partners, project managers, and other domains to build analytics capabilities and drive business value.
Master's degree in a quantitative field including but not limited to data science, analytics, and statistics and 2-3 years of data science experience or bachelor's degree and 3-5 years of data science experience.
Experience in one or more of manufacturing, retail operations, new product development, supply chain or marketing research (incl. digital media, subscription packages, market analysis).
Ability to work with large data sets from multiple data sources.
Basic proficiency in Machine Learning.
2 years of programming experience in statistical software (for example Python, R, or SAS). Some Python experience preferred.
Prior experience participating in projects using common project management methodologies e.g., Agile, Waterfall, Six Sigma, Lean.
Able to support the building of business cases related to data science related projects.
Enjoys working collaboratively with other data scientists and multiple stakeholders across the business unit and with external partners.
Able to solve problems and brainstorm options to solution a given problem.
Intellectual curiosity, a passion for data and a results orientation.
Prior experience operating and deploying models in cloud environments e.g., AWS & Azure
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